Healthcare data breaches average $10.93 million, more expensive than in any other industry. Thankfully, improvement is possible. Artificial intelligence (AI)-enabled anonymization techniques can hide sensitive details so these breaches don’t impact patient privacy. Here are five of these methods you’ll see in health care today.

1. Pseudonymization

The most basic of these anonymization techniques is pseudonymization. As the name suggests, this practice replaces personally identifiable information (PII) with fake details that serve the same purpose.

Replacing a patient’s name with “John Doe” won’t change any health details, so it’s useful but won’t reveal who it’s talking about if breached. The downside is that someone could theoretically reidentify the record with enough work. For that reason, the Health Insurance Portability and Accountability Act (HIPAA) says pseudonyms cannot come from related information about the patient — they must be entirely random.

2. Tokenization

“Tokenization has saved $650 million in fraud in the finance industry in 2023, so it has huge potential in the health care sector, too.” 

Tokenization is a similar but more complex method. Here, an AI algorithm generates a unique placeholder for PII in a health record. Like pseudonymization, the data is still usable for treatment and analysis without sacrificing privacy. However, it’s different in that it uses cryptography to generate these stand-ins, reducing the likelihood of reidentification.

Many tokens are temporary, so they change between functions to offer even more privacy. This practice has saved $650 million in fraud in the finance industry in 2023, so it has huge potential in the healthcare sector, too.

3. K-Anonymity

A less common but equally beneficial approach is to use K-anonymity. This method applies various masking techniques to keep the overall value of a dataset the same while changing the exact identifiers. For example, it could change all the names and addresses of a hospital’s patients but still contain the same levels of each demographic.

Because K-anonymity applies to entire datasets instead of individual records, you can’t use it for individualized applications. However, it’s still useful for medical research, such as tracing health trends across a population.

4. Dynamic Data Masking

Sometimes, the amount of PII you should remove depends on the situation. Dynamic data masking (DDM) serves this need by changing how much information it hides depending on the context. That could mean removing more details when users with less authorization access it or removing more PII for machine learning applications than patient care cases.

HIPAA requires role-based access controls, and DDM makes it easier to implement these restrictions. Using AI to determine who can access what data simplifies this decision-making, enabling faster care while preserving privacy. 

“Sometimes, how much PII you should remove changes depending on the situation.” 

5. Synthetic Data

Synthetic data is unique in that it eliminates all PII from a database. Here, machine learning models generate entirely original information that mimics the real world. The resulting dataset looks and behaves like patient data but contains no basis in reality.

This method is the most secure option, as it has no ties to actual patients’ information. However, for that very reason, it’s also of limited use in health care. You can train AI models with it, but it won’t work for research or patient care applications.

Choosing a Data Anonymization Method

“Health care organizations shouldn’t rely on a single data anonymization method. Instead, you should employ various techniques depending on the specific use case.” 

The best anonymization technique depends on your needs and goals. You can determine the optimal method by first reviewing any applicable regulations. That includes more than just HIPAA. For example, the International Medical Device Regulators Forum is a voluntary code, but partner organizations may look for it for assurance of higher standards.

These regulations may specify which methods are applicable for different types of data or situations. For example, you may be able to use pseudonymization for low-sensitivity tasks but must use tokenization or DDM for those involving more data sharing or vulnerabilities.

Similarly, you should consider your end goal. Masking techniques like pseudonymization and tokenization are not as secure but enable personalized health care. Synthetic data isn’t useful in that area, but it improves machine learning accuracy and maximizes security.

Given these complex considerations, healthcare organizations shouldn’t rely on a single data anonymization method. Instead, you should employ various techniques depending on the specific use case. Matching each application to the anonymization method that fits it best will produce the optimal balance between security and usability.

Health Care Data Needs Extensive Protection

Healthcare data is more sensitive — and, as a result, a bigger target for cybercrime — than any other form of information. In light of that risk, the medical industry must embrace privacy wherever it can. Anonymization is an important part of that goal.

These five methods are not the only ways to anonymize data. However, they are some of the most popular and effective strategies. Learning how each can benefit your workflows is key to protecting patient privacy while leveraging new technology.

Also, Read How Is AI Transforming the Landscape of Medical Technology?

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The medical industry faces higher standards than most, so new technologies take a while to become common in this sector. The growth of AI surgery robots has been slow, but some models are already in use. Many others show substantial promise in their early development stages. Here’s a closer look at how these technologies could transform the industry.

Going Where Human Hands Can’t

“The most obvious advantage of AI and robots in the OR is that machines often have finer motor control than humans. That means surgery bots can work on patients without needing large, invasive cuts while reducing the risk of errors.” 

Despite surgeons’ extensive training, roughly 4,000 surgical errors occur in the U.S. each year. Some of these stem from tiredness or distraction — something AI can’t experience. Others come from the difficulty of operating in tight, sensitive spaces, which smaller, more precise robotic controls make easier.

Early robotic surgery examples have resulted in fewer complications and blood loss. These robots don’t replace human surgeons entirely but use AI and robotic assistance to operate in smaller spaces with less motion as surgeons guide them. As AI improves, it could further help by recognizing emerging complications and adjusting automatically or alerting doctors to prevent further injury or mistakes.

Making Medical Implants Less Intrusive

AI-powered robots can also help outside of surgery itself. Robotic surgical implants can monitor patients’ post-operation health or administer medication over time to ensure better ongoing health. AI makes these implants less disruptive and more effective.

Unlike their industrial counterparts, these robots are typically made of materials like liquid silicone rubber, which is resistant to bacterial growth and hypoallergenic. This soft material also lets them sit in patients’ bodies without disturbing the tissue around them, preventing complications. Some even use AI to detect and move in response to changing tissue conditions to avoid scarring.

AI also lets robotic implants determine when to inject certain medications and how much of them to administer. That way, patients get the care they need, even as their bodies change. This more personalized approach to health care promotes better patient outcomes.

Enabling Remote Surgery

“One of the most exciting applications for AI-powered OR robots is remote surgery.” 

Some of the same surgical robots that improve in-person surgery precision support remote operation. Hospitals can use these to bring leading medical care to more people across the world.

Remote surgery is particularly important in light of how the world will be short 10 million medical workers by 2030. With conventional methods, that means patients in some areas may be unable to access life-saving surgery without traveling, which introduces further risks. Remote-controlled robots mean experts on the other side of the world can operate on these patients to address that gap.

AI makes this technology more reliable. Lag and errors from not seeing things in person can cause potentially dangerous mistakes in remote surgery. AI can detect these issues and counteract them in real-time to prevent errors and ensure patient safety.

AI and Robotics Will Usher in a New Era of Medicine

AI-guided robots likely won’t replace human surgeons, especially anytime soon. Rather, they assist them so they can use their talents to their full potential.

As technology improves, the potential for AI and robotics in surgery will only grow. These innovations have already improved the OR in many ways despite their relative newness. It’s safe to say that this trend will continue in the future, leading to new levels of patient safety and healthcare accessibility.

Also Read The Real Impact of AI in the Workplace

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As machine learning techniques have improved, more medical manufacturers have turned to AI to streamline and refine their quality assurance (QA). It’s easy to see why since AI’s QA benefits apply across the entire production timeline.

Speedier R&D

AI’s advantages in pharmaceutical quality control begin in the research and development (R&D) phase. Machine learning models can simulate drug interactions to reveal which compounds might be the most promising candidates for new medicines without time-consuming real-world tests.

This speed and accuracy allowed Moderna to synthesize and test over 1,000 mRNA strands a month when researching COVID-19 vaccine candidates. Conventional, manual methods could only produce 30 strands in the same time frame.

AI can streamline the clinical trial process after selecting an ideal drug candidate. It starts with machine learning predicting at-scale real-world outcomes based on lab tests. From there, AI models can also analyze demographic data to highlight ideal areas and populations to test a medicine for greater participation.

These AI applications lead to less time in the planning phase while improving R&D accuracy. As a result, pharmaceutical products reach higher quality standards from the start without taking more time.

Fast, Accurate Error Detection

AI offers a more efficient alternative to manual quality inspections in the production process. End-of-line QA checks typically create bottlenecks, as closely inspecting products is much slower than the manufacturing speed. That’s especially the case with pharmaceuticals, where processes like cryo grinding can produce particles just 10 micrometers or smaller, requiring highly precise inspections.

Machine vision can perform these inspections much faster than humans. They can identify defects immediately because they compare products to hard data on what passable items look like. Consequently, some AI quality inspection systems can analyze pharmaceuticals as quickly as production lines make them.

On top of being faster than humans, AI is also more accurate. Medicine QA checks are highly detail-oriented. Humans struggle to perform these tasks without mistakes, but AI delivers the same standard every time.

Minimizing Human Error in Production

AI also streamlines QA in pharmaceutical manufacturing by making the production process less error-prone. Just as machine vision minimizes mistakes in quality testing, similar AI applications prevent them in production.

Collaborative robots significantly improve assembly precision, and AI features like machine vision make them more adaptable. Consequently, automated machines can deliver that accuracy even when other conditions change. Human and machine-related errors decrease as a result.

AI can also analyze digital twins of production lines to highlight where errors occur. Some models can even suggest potential changes, helping pharma companies refine their workflows to make quality mistakes less likely.

These AI-driven improvements mean medicines are less likely to have flaws before reaching the final QA inspection. By preventing mistakes instead of simply identifying them, pharmaceutical manufacturers minimize time spent removing defective medicines or fixing errors. Their product quality and production efficiency increase as a result.

AI Could Revolutionize Pharmaceutical Manufacturing

Pharma manufacturers face increasing pressure to improve their throughput and QA as attention around public health issues grows. Doing that with entirely manual workflows is challenging. AI provides the accuracy and speed these companies need to meet both sides of this demand.

AI is already making waves in pharmaceutical manufacturing, especially in the R&D phases. As this trend continues, more pharma companies will catch on and implement this technology in their processes. Slowly, the entire industry will reach higher efficiency and quality standards, all thanks to AI.

Also Read How Generative AI Has Revolutionized Robotic Surgery

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Attention to mental health in the workplace rose around the same time as remote work. Given this trend, it’s important to recognize management’s role in remote workers’ well-being.

Regular Communication

“Working from home is inherently more independent, which can make some employees feel disconnected or unsure of what’s expected of them.” 

One of the most important mental health steps for remote team managers to take is to communicate. Working from home is inherently more independent, which can make some employees feel disconnected or unsure of what’s expected of them. Thorough communication addresses these feelings.

Regularly check in with your remote staff to answer questions and discuss their current goals and struggles. Communication technology like video-conferencing software improves these discussions by offering face-to-face connections to boost empathy. Centralized project management platforms can help, too, as they make it easier to understand work expectations and requirements.

As helpful as regular communication is, you must also consider that 69% of remote employees feel increased burnout from digital communication. Using asynchronous collaboration software for most conversations and saving instant messaging or video calls for urgent matters can offset that burnout.

Enable Flexibility

“71% of teleworking professionals say working from home helps them with their work-life balance and 56% say it makes it easier to meet deadlines.” 

It’s also important to lean into what makes remote work desirable to team members in the first place. Flexibility is a common one — 71% of teleworking professionals say working from home helps them with their work-life balance and 56% say it makes it easier to meet deadlines.

Giving remote workers more flexibility will help them make the most of their already flexible work arrangements. This may look like letting employees set their own schedules or letting them practice more creativity in how they approach a project. When workers have this freedom, working independently or lacking specific guidelines is often more comfortable, preventing stress.

Remote work setups that look too much like a conventional office workflow may minimize the mental health benefits of working from home. Strict guidelines or scheduling policies can make remote work feel less relaxed and make it harder to log off when the day should be over.

Promote a Healthy Work-Life Balance

On one hand, flexible work arrangements provide more freedom to balance work and personal life. However, on the other, they also make it easier to lean too far into the home side of things, leading to an unhealthy balance.

Encourage employees to practice healthier work habits. These include having a dedicated office space, following a semi-regular work schedule and silencing notifications while working. Dressing professionally can help, too, as experts say it sets the tone for the day.

Practicing these behaviors yourself will assist by setting an example for your team. You can also encourage them by providing a list of tips for maintaining a healthy work-life balance and bringing it up regularly.

Provide Mental Health Resources

Of course, no mental health program is complete without providing more formal health care resources. You should offer your remote employees access to things like therapy or meditation apps just as you would connect them with physical health insurance.

Offering these resources to remote teams requires a digital approach. Consider covering online therapy platform subscriptions or a cloud-based remote employee assistance program. You can also provide links to pages explaining common mental health challenges and solutions for remote workers.

Once you offer these resources, you must promote them. A shocking 85% of employees with mental health coverage from their workplace don’t use these programs. That gap comes mainly from not knowing they have this access and them being hard to use. Better communication and prioritizing accessibility will address that issue.

“No mental health program is complete without providing more formal health care resources.” 

Run Team-Building Sessions

Finally, you should consider ways to foster team spirit among remote workers. Because working from home is so independent, they often feel isolated socially and professionally. Remote team-building is the answer.

Host group video conferences regularly to foster more camaraderie and remember to keep these meetings relatively casual. Running games, watch-alongs or other fun activities outside of work hours on these same platforms can help fight loneliness, too.

Remember — any non-work-related team-building activities must be optional. If you make them mandatory, they’ll feel less relaxed and may worsen engagement and well-being.

Remote Work Brings Unique Mental Health Challenges

Remote work didn’t create the issue of workplace mental health challenges, but it presents some unique obstacles. While these flexible setups can be highly beneficial, managers must remember to address the increased loneliness and stress that can come with them.

Thanks to digital technologies, you don’t have to sacrifice communication or inclusion for remote productivity. These five steps will help you support your staff’s well-being, regardless of their distance from the office.

Also Read 5 Tips for Using AI to Unlock Employee Productivity

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1. OR Black Box

This sophisticated system of sensors and data recorders captures every detail during surgical procedures. Specifically, the Black Box monitors all factors that might affect the results of a procedure — patient vital signs, equipment malfunctions, anaesthesiology and more.

The information collected provides a rich resource hospitals can review to improve OR safety. For instance, Duke University Hospital surgeons use these black boxes to enhance communication and improve patient positioning during surgical procedures to minimize nerve injury risks.

Data from the system can also shed light on possible improvement areas. It’s all about generating top-notch information, according to Teodor Grantcharov, MD, PhD, inventor of the OR Black Box. To ensure the confidentiality of staff and patients, the data capture system blurs faces, distorts voices and deletes recordings after 30 days.

“…Duke University Hospital surgeons use these black boxes to enhance communication and improve patient positioning during surgical procedures to minimize nerve injury risks.” 

2. SurgiBox

One of the main distinguishing features of an OR is sterility. Surgical site infection is a genuine concern, already affecting 3% of patients undergoing operations. However, emergency procedures can’t always wait for a clean room, as is the case in war zones and areas hit by natural disasters. SurgiBox is a portable OR kit surgeons can use to create sterile operating environments.

The system includes an aseptic bubble with inward-facing armholes for the surgeon. There’s a smart module attached to regulate airflow, and a rechargeable battery pack to power medical equipment and emergency lighting. Everything fits neatly in a backpack. Obviously, SurgiBox is not as hygienic as an actual OR, but it’s about as safe as it can get if you look at it in the context of where it’s being used.

3. AI-Assisted Surgeries

Robot-assisted surgeries have been around for some time now with scores of success stories. With artificial intelligence and deep learning capabilities, these robots are smarter and more capable than ever.

In addition to their highly advanced physical capabilities, AI-enabled robots can analyze surgeries in real time and provide decision support to surgeons, improving their precision. According to recent research, AI-assisted procedures resulted in five times fewer complications than surgeons operating alone.

Advanced algorithms can also detect anomalies more accurately, allowing surgeons to target affected areas more precisely. For instance, in colorectal surgery, machine-learning tools can analyze pre-operative scans to identify vulnerable regions, reducing the chances of inadvertent damage and improving decision-making.

“…AI-enabled robots can analyze surgeries in real time and provide decision support to surgeons, improving their precision.” 

4. Smart Operating Rooms

A smart OR features ergonomic upgrades and integrated state-of-the-art functions for improved safety and efficiency. Effortless human-machine interaction is crucial in a theater full of delicate medical equipment, which is where ergonomics comes in.

Smart ORs facilitate real-time consultations with other specialists outside the room, allowing them to provide remote assistance without delay. This function can mean the difference between life and death in complicated surgeries.

5. Internet of Medical Things (IoMT)

IoMT enables real-time machine-to-machine interactions and data streaming using cloud connectivity. These interconnected devices provide dynamic information on a centralized hub to improve patient safety in the operating room. For example, access to the same surgical status data frees up circulating nurses to keep their focus on the patient rather than staring at different screens looking for specific info.

IoMT machines can also make operations more efficient. For instance, using a laparoscope for image-guided surgeries can minimize tissue damage and blood loss by providing a clearer, real-time view of the body during the procedure.

“[A]ccess to the same surgical status data frees up circulating nurses to keep their focus on the patient…” 

Technology Is Shaping the Future of Surgery

As medical innovations continue to advance, the future of surgery will likely feature increased autonomy with integrated machine learning. The WHO estimates a shortfall of 10 million health workers globally by 2030. These technologies help fill the gaps where the system is running short. For example, remote surgery can bring life-saving expertise to remote areas without specialized health care facilities. 

AI-powered surgical robots should also become more mainstream. Its global market is growing fast and is expected to reach a valuation of $25.7 billion by 2032. In turn, this can lead to an increase in demand for minimally invasive surgical procedures. 

Tech for Safer Operating Rooms

Health care will always be people-centric, but technology has its place in ensuring a well-rounded experience. By providing the ability to observe real-time data and respond to situations quickly, these innovations facilitate more precise surgery and less chance of complications. This collaboration will only get better over the years, resulting in safer, more efficient surgical environments.

Also Read AI’s Contributions to Underwater Environmental Protection Efforts

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“Artificial intelligence can potentially revolutionize this part of the medical care industry” 

Here’s how doctors and researchers have begun testing AI for blood transfusions and the implications this practice could have on the health care industry in the future.

Monitoring Patients During Transfusions

Many recipients of blood transfusions are older adults or have altered mental status. Consequently, someone has to monitor them during the process to ensure they don’t bend their arm or remove the IV. 

However, a whole blood transfusion can take two to four hours. Nurses overseeing at-home transfusions may need to leave the room at some point and don’t always have another person to step in while they’re out. This could put patients at risk of accidentally harming themselves.

That’s why Wakayama Medical University Hospital researchers have started testing an AI algorithm that monitors patient movement during blood transfusions. The software uses Python to determine initial body position. The AI can tell if someone bends their arm and notifies a physician. The doctor can watch the footage on a smartphone and contact the attendant if needed.

Researchers have only used the software in a pilot study so far. However, it shows great promise for aiding attendants during blood transfusions, especially in the home health setting. 

Preventing Errors

Doctors must always match patients with a compatible blood type for a transfusion. Otherwise, the results can be disastrous — even fatal. As the patient’s immune system attacks the foreign cells, their blood may form thick clots that end up killing them.

Blood banks and doctors thoroughly check donated blood before administering it to a patient. They screen it for ABO type and check the Rh factor, among other things.

Still, accidents happen, usually because of human error. An estimated one out of every 19,000 units of red blood cells is given to the wrong patient annually. One in 1.8 million cases of red blood cell transfusions causes a fatal hemolytic reaction every year. 

“AI has the potential to save lives by double-checking donated blood for compatibility before doctors transfuse it.” 

It can assist in matching blood types and distinguishing subpopulations of cells within a sample. AI can help doctors spot health issues sooner and learn about the risk factors of certain blood going to specific patients.

Minimizing Overuse

Another human error may have fewer dangerous effects on patients but can waste donated blood. According to the U.S. Food and Drug Administration Center for Biologics Evaluation and Research, many health care systems overuse transfusions by giving one that may not be strictly necessary. This better-safe-than-sorry method can waste blood badly needed by more critical patients. 

Now, researchers are working on developing an AI-based blood utilization calculator. This calculator can potentially guide doctors’ decisions on whether to transfuse blood and how much to use for a patient. The up-and-coming technology is promising for use in health care settings and can be beneficial in emergencies. 

Locating and Profiling Potential Donors

One potential use for AI in blood banking is to look at available data to find donors. This would be especially beneficial during disasters when blood is urgently needed. For example, AI could:

• Track blood donor behavior after donation
• Check for seasonal variations among donor types
• Develop metrics for repeat donors
• Identify what motivates people to give blood
• Look at the cognitive, demographic and psychological characteristics of blood donors

Compiling this data could be very useful for retaining existing blood donors and attracting new ones, especially in emergencies.

Developing New Blood Products

“A physician-scientist from the University of Maryland School of Medicine (UMSOM) is leading a research program to develop a new artificial blood product.” 

It would be stored at room temperature and could save victims of warfare, gunshots or car accidents within minutes of first responders arriving on scene. 

The product will combine synthetic elements like artificial oxygen carriers and freeze-dried plasma to help it remain stable outside the fridge. It will be able to deliver oxygen, replace blood volume and stop a patient’s bleeding just like real blood does. 

Researchers are using AI, experimental platforms, and animal models to develop and test the therapy. They are also trying different manufacturing and packaging methods to make the product more practical to use in the field. 

A Synergistic Partnership

Because blood transfusions often occur during emergencies and have so much potential for error, they will always require a medical professional to be present. The human touch also comforts patients during what can be a very stressful procedure. 

Still, AI is an extremely valuable asset to doctors and nurses. Algorithms can check blood for donor compatibility, reduce overuse, help develop new therapies and locate potential donors. In the future, AI will certainly have a place in every hospital.

The post How an Algorithm Could Help Improve Blood Transfusions appeared first on AiiotTalk - Artificial Intelligence | Robotics | Technology.

Enabling a Remote and Visual Way to Check Blood Pressure

High blood pressure increases your risk for heart attacks, stroke, artery damage and more. However, many individuals don’t even know they have it. A complicating factor is that nervousness can cause high blood pressure in the doctor’s office but not elsewhere. 

“An AI-based tool achieved approximately 90% accuracy with a visual method of checking blood pressure.” 

Issues can also arise if doctors instruct people to regularly take their blood pressure at home. Improper cuff sizes can give incorrect results, as can crossing your legs or not sitting up straight when taking a reading. However, researchers have developed a method that allows you to provide blood pressure readings from home and eliminate these issues. 

Their method uses AI and a digital camera to capture cardiac signals from two areas on a person’s head for 10 seconds. This method achieved about 90% accuracy compared to conventional blood pressure measurement methods.

The researchers tested their approach on 25 people with different skin tones exposed to varying light conditions. They believe this method could be particularly advantageous when it’s less safe or impractical to take people’s blood pressure in the usual way, such as during the COVID-19 pandemic. 

Supporting Human Judgment in Intensive Care Units

Medical professionals in intensive care units must rely on patient data and experience to make the best decisions as situations develop. Even so, their jobs pose continual challenges since health conditions can deteriorate rapidly. 

“Researchers developed an AI treatment support tool that caused a 3% improvement in sepsis cure rates.” 

Researchers realized they could train AI algorithms to detect how patients’ states changed over time, and then make appropriate care decisions. They taught the artificial intelligence application to patients with sepsis. They believed the blood-poisoning condition showed partial potential since it has a high fatality risk that rises significantly without early detection. 

The training involved reinforcement learning, which rewards or penalizes the algorithm based on the correctness of its decisions. The team made the algorithm use vast quantities of medical data to find the most likely successful treatment strategies. 

Experiment outcomes showed the algorithms became better than humans in suggesting care options. One experiment showed an approximate 3% improvement in the cure rate with this method. 

Although the research team does not advocate for letting AI make decisions without human supervision, they believe their technology could support doctors’ choices and be valuable in medical education applications. 

Reshaping Medical Sample Collection

Healthcare management requires the ongoing participation of many people with specialized training. For example, medical technologists are instrumental to patient care by performing diagnostic tests that tell physicians which treatment paths to pursue. 

“Robots can perform blood draws and COVID-19 tests, relieving labor shortages.” 

Some people have investigated whether AI could improve the methods of collecting samples from patients. Consider how European medical technology company Vitestro developed a blood-drawing robot that handles needle insertion and gathers the liquid. The company has tested its prototype on more than 1,000 people and intends to sell the device in 2024 to European customers. 

Company officials believe their innovation could reduce the strain caused by a worldwide phlebotomist shortage. Not having enough qualified individuals to conduct blood draws makes it take longer for patients to receive proper treatment. 

Similarly, a Chinese company developed a robot that can test people for COVID-19 much faster than current methods. The invention, which looks like a vending machine, can process 320 samples at once and provide results for 80 people every 45 minutes. 

Monitoring Older Patients Through Contact-Free Means

As you age, you may face the challenges of continuing to live independently without putting yourself in danger. People with balance or hearing issues are at greater risk when living alone. However, they don’t necessarily need to be transferred to a supervised facility.

Researchers have created an artificial intelligence tool that uses a wireless transmitter to send low-power waveforms across indoor spaces. A receiver gathers the information as the waveforms bounce off people and objects in the environment. An AI engine then processes that data and extracts insights about the resident’s activity levels. 

The team said this technology does not require wearable devices — which users often find cumbersome. Instead, it mounts on ceilings or near walls and works without cameras. However, it can detect possible urinary tract infections, decreased activity levels or the increased likelihood of falling. 

Tools like this could be advantageous for helping older people retain their freedom and autonomy without potentially risking their health. Similarly, it could provide peace of mind for the person’s loved ones who want assurance that they’re safe and well. 

AI Will Advance Medical Technology

Although many medical technologies don’t use AI, these examples show that artificial intelligence can often improve results and optimize patient care decisions. You should expect AI to continue playing a significant role in developing potentially life-changing devices.

Also, Read Leveraging Artificial Intelligence To Reduce Plastic Waste

The post How Is AI Transforming the Landscape of Medical Technology? appeared first on AiiotTalk - Artificial Intelligence | Robotics | Technology.

Between human consumption, animal feed and serving as a feedstock for other resources, cereals play a critical role in life and industry. Therefore, protecting them is essential for the economy and for ensuring the health of many.

Mycotoxins present a significant threat to cereals. The fusarium mycotoxin, in particular, has become an increasingly pressing issue, but artificial intelligence (AI) may help. Broader AI implementation could mitigate current infections and prevent future ones. Here’s how AI can aid in keeping food supplies safe.

What Is the Fusarium Mycotoxin?

Mycotoxins are a kind of contaminant from fungus and are toxic to humans and animals. About 60%-80% of crops worldwide have some level of mycotoxin contamination, with  20% of these infections exceeding food safety limits.

Fusarium is a class of mycotoxin affecting cereals like wheat and oats. It covers several specific fungus species and toxins, but all affect humans and livestock. Even when it’s not in high enough concentrations to be dangerous to people, it can limit cereals’ nutritional content, making it difficult to feed growing populations. Fusarium mycotoxin is becoming increasingly common.

“Climate change and modern farming practices have made conditions more conducive to fusarium growth and spread. If this trend continues, it could affect food scarcity, livestock health and industrial feedstocks.” 

How AI Can Help

Recent fusarium growth is worrying, but cereal farms can take action against it. Here’s how AI can help catch, mitigate and prevent fusarium mycotoxin risks.

Accelerating Mycotoxin Research

The first step in fighting fusarium is learning more about it. Scientists and farmers can take more effective measures against mycotoxin when they know what conditions promote contamination. AI excels at noticing trends in data, making it the ideal tool to accelerate this research.

Some machine learning models have achieved more than 75% accuracy when predicting which corn fields had mycotoxin contamination. They use various data, including weather patterns and cropping methods, to identify when conditions are right for mycotoxin growth. Using them across more farms could help scientists understand how and why these contaminants grow.

Similarly, AI can analyze past research and compare it to new data to highlight trends and correlations researchers may miss otherwise. AI also performs this kind of analysis faster than humans, leading to quicker breakthroughs to prevent fusarium-related losses.

Predicting Outbreaks

Predictive analytics models can also help farms predict outbreaks before they occur. Data from the research algorithms can let other AI models act on these historical trends to determine when a harvest will likely contain fusarium. Some early examples have shown up to 94% accuracy in these predictions.

These predictions can let farmers account for losses ahead of time. Farmers that know a certain percentage of their crops may be unsuitable for human consumption can let downstream supply chain partners know to minimize last-minute disruptions. They’ll also learn to watch the harvest more closely, reducing the chances that something will slip through the cracks.

Early, informed responses are key to preventing health risks and avoiding large supply chain disruptions. Crop losses aren’t as impactful if companies have time to adapt. Consequently, AI’s speed and reliability can save farms and businesses that rely on them considerable amounts of time and money.

Monitoring Storage Conditions

Another way AI can address fusarium risks is by monitoring cereals in storage. Even after harvest, mycotoxins can accumulate on crops in the right humidity and temperatures. Farmers can stop this growth short if they catch it early enough, and AI provides that agility.

Internet of Things (IoT) sensors can monitor humidity, temperature and other factors contributing to mycotoxin growth in storage tanks. AI can analyze this data to alert relevant employees when these conditions near risky levels. Workers can then adjust climate control settings to prevent fusarium growth or inspect grains for contamination.

Similar systems can also monitor grain shipments in transit. That way, logistics providers can ensure crops stay in prime condition throughout the supply chain, preventing food loss. Trucks can pull aside to inspect the shipment or alert downstream partners if a problem is detected.

Streamlining Testing

AI can also make testing processes more efficient. Inspecting grains for mycotoxin is crucial, but conventional approaches may involve running four individual tests in sequence, taking considerable time. AI can perform needed analysis far faster than these traditional methods, providing quality assurance without excessive disruption. The manufacturing industry is an excellent example of AI’s potential for quality control.

“Many manufacturers use machine vision systems to analyze hundreds, even thousands, of products a minute with near-zero error rates.” 

Similar methods can scan cereal grains for fusarium and other mycotoxins without invasive, time-consuming testing.

Faster testing’s benefits go beyond supply chain efficiency. It also enables quicker responses, helping agricultural companies minimize waste to protect food supplies and prevent economic losses from product loss.

Tracing Contamination

Preventive measures are best when possible, but it’s also important to respond to contamination incidents that get through. AI can continue to help in these scenarios by providing more visibility into an outbreak’s origins.

Responses to the COVID-19 pandemic proved AI’s potential for outbreak tracing. Some algorithms could identify an outbreak’s zone with 100% accuracy, whereas non-AI systems failed to produce reliable results. Similar techniques could analyze agricultural supply chain data to determine where fusarium contamination cases originated.

This traceability would help identify cereal grain shipments that may be affected, informing additional testing to prevent illnesses. It would also refine prediction algorithms by providing more insight into how these outbreaks start and spread.

AI Can Protect Public Health and Improve Farming Returns

Climate change makes the threat of fusarium mycotoxin more prevalent, and understanding and addressing these outbreaks is increasingly important. AI could be a critical piece of that puzzle, thanks to its accuracy and speed in data analysis.

These five use cases highlight AI’s potential for preventing and mitigating mycotoxin-related risks in cereal grains. Implementing them will ensure safe food supplies for people and animals and avoid supply chain losses in the farming industry.

Also, Read How the Pharmaceutical Industry is Harnessing Emerging Technology

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In this article, we will explore just a few of the ways in which pharmacists are utilizing new tech — and how these resources may change the face of the industry. 

Accessibility

Robotics and automation are swiftly becoming key resources within the medical field, and one of the main benefits they provide is a greater level of accessibility for patients and service users.  

The pharmaceutical sector is no different: through the application of various technologies of this kind, patients can find answers to their questions, self-test for some conditions and even order prescriptions 24/7. 

Responsibly programmed automated chatbots can respond to queries and offer advice to individuals communicating with pharmacy services out of hours, speeding up processes, reducing the workload of medical professionals and providing patients with peace of mind. 

From signposting relevant services to suggesting potential treatments, systems of this kind can make a huge difference. Certain straightforward procedures, such as hearing and allergy tests, can now be taken at home using available technologies. 

Not only does this save time and resources for pharmacists, but it also means that individuals with reduced mobility or little access to transport or funds may easily access these services. Operatives within the pharmaceutical sector may even choose to offer 24-hour collection.  

“A service system similar to the parcel lockers used by Amazon and other delivery companies allows patients to sign up, have their prescriptions fulfilled, and leave the required items in a secure, PIN-accessible lockbox for them to collect at their convenience.” 

This allows improved access for those whose schedule does not allow for 9–5 prescription collection. 

Medication and Health Monitoring

Pharmacists and pharmacy operatives across the world face a particular challenge in monitoring uptake and regulating patient compliance.

Naturally, the efficacy of most drugs and treatments depends on the user’s adherence to instructions on how — and when — to use them.  

This can prove something of a pitfall, as many patients are very busy and may forget or put off taking medications, while others may be mistrustful of certain drugs. Some facing cognitive challenges may forget altogether or actively reject their treatment. 

Today, new technologies and systems are in place to remind patients of the correct time to take their medications, and some of these technologies can even be programmed to collect feedback on the long-term impact of a specific drug.

By asking the user to input information on the severity of their symptoms at different stages throughout their treatment — while concurrently reminding them to take their medication on time and dispensing it with suitable regularity — these systems offer an almost comprehensive service. 

The data collected can then be fed back to the prescribing pharmacist, helping them to track progress without the need for direct and accurate reporting from the patient. 

Digiceuticals

“‘Digiceuticals’ refers to particular technologies usually mobile or tablet applications that offer therapeutic support for patients who need to monitor and manage their health on an ongoing basis.” 

This may include individuals who are facing issues such as: 

• Nicotine addiction or reliance on other substances. 
• Anxiety, depression or other mental health challenges. 
• Insomnia, eating disorders or neurodivergence. 
• Conditions requiring ongoing physical therapy exercises. 
• Diabetes and other chronic, life-limiting or debilitating conditions. 

These digital tools can help users to manage practical tasks such as undertaking of regular physical therapy exercises or the checking of blood sugar levels or blood pressure. At the same time, they may also provide cognitive behavioural therapy (CBT) or behaviour modification support.

When used in conjunction with medications and other treatments — or, indeed, as stand-alone resources — these applications allow patients greater autonomy, flexibility and personalization when it comes to the management of their condition, as well as freeing up the working hours of medical professionals. 

Risk Management

Many medications come with adverse side effects, and the recording and evaluation of these constitute an important aspect of data collection and analysis within the pharmaceutical sector. 

Not only can AI and automation streamline the collection of information and its addition to national databases — enabling the probability of certain severe side effects to be more easily calculable — but there are also technologies that create a ‘drug profile’ for certain patients. 

The profile considers the medications currently utilized by an individual, and whenever a new treatment is prescribed, it undergoes a cross-check with the existing regimen. If the combined treatments are known to have adverse effects, the system flags this, significantly reducing the risk of severe reactions and overprescription.

Another risk that can be more effectively managed through the application of advanced technology is that of antibiotic resistance. Without due care, certain bacteria may develop an immunity to antibiotic treatment — resulting in highly contagious strains that are tougher to treat and may potentially cause dangerous epidemics. To ensure the responsible use of antibiotic medications, it is crucial to prescribe them appropriately and ensure that patients complete the full course of treatment each time. 

“New developments in pharmaceutical technology enable the intelligent collection and analysis of data, generating alerts that can be accessed by all parties involved in a patient’s treatment.”  

These alerts indicate when the use of antibiotics would be suitable and when alternative approaches should be considered before resorting to antibiotics. The issue of antibiotic resistance has long been a subject of intense focus and study within the industry for many decades.

However, those now beginning their studies in order to pursue PharmD careers may well graduate into a world where technological advances allow far easier management of antibiotic prescription. Earning a Doctor of Pharmacy degree allows graduates to work alongside doctors, nurses and other medical professionals, recommending and managing medications. They may sometimes assess patient health and make recommendations. 

Indeed, PharmD courses themselves have undergone something of a technological revolution, with many — such as the one offered by the University of Findlay – available on a remote, ‘distance-learning’ basis. 

Conclusion

The development and implementation of new technologies within the sphere of pharmaceutical research and practice are vital to its growth and improvement. It will serve to boost the efficacy of treatments, processes, communication, access, affordability and many more aspects. 

Of course, many new tools rely on the collection of data, which must be undertaken responsibly and with suitable consent — and conversations are ongoing regarding the proper monitoring and management of AI and machine-learning systems. 

There is also the challenge of patient uptake. It will inevitably be more difficult to successfully encourage the use of new tech by patients who have a distrust of technology or limited computer literacy. However, if hurdles of this kind can be surpassed, the potential of these emerging technologies promises to be extremely impactful — and possibly revolutionary.  

Also, Read How Artificial Intelligence Is Altering the Health Care Industry

The post How the Pharmaceutical Industry is Harnessing Emerging Technology appeared first on AiiotTalk - Artificial Intelligence | Robotics | Technology.

But because of your niche, healthcare email marketing looks slightly different from other industries. Here are five strategies to build and maintain a list for medical practices.

5 Ways to Create and Grow a Healthcare Email Marketing List

“Think of email marketing as a stranger who knocks on your door. Would you let it in if you do not trust it? The answer is no.” 

That is why it requires a well-thought-out plan to work, especially if you are in the healthcare industry. The information you share can potentially save a life.

Consider these pointers when building and nurturing your subscribers:

1. Do Not Violate HIPAA for Marketing

Because you are handling and storing patient health information (PHI), you should abide by the HIPAA rules for promoting products and services. In hindsight:

• Always ask subscribers to opt into the mailing list. Get their consent to give you their email address. Let them sign a form if they visit your clinic or include a detailed note on your website. Share how you plan to use their data.
• Limit access to sensitive information. Create different levels of security controls for those involved in email marketing.
• Allow subscribers to opt-out. Include an unsubscribe button on your emails. Guarantee you will not send them any more mail after they remove themselves from the list.
• Do not share PHI on marketing materials. However, you can use aggregated information, such as statistics, in your emails and articles.

2. Hyper-Personalize Emails with Segments

People have various motivations for subscribing, meaning not everyone will buy a product or book an appointment—ever.

How do you ensure that you can focus on high-value leads instead? The answer is hyper-personalization.

According to Digital Authority Partners (DAP), personalizing emails suggests breaking down subscribers into various categories. Hyper-personalizing implies further segmenting members of each group. This way, you can:

• Weed out unqualified leads and subscribers who will never amount to anything
• Nurture those in the awareness stage with helpful content
• Engage those who are ready to buy or book an appointment
• Reengage subscribers who have not interacted recently

Here are a few ideas to make this strategy work:

• Understand your ideal audience more deeply. Go beyond demographics and incomes. Learn about their culture, buying behavior, influences, and pain points.
• Conduct surveys and interviews. Encourage subscribers to answer questions that may help you know their challenges in accessing emails, the content they wish to see, or the tone you should use.
• Use artificial intelligence (AI) and machine learning. These tools leverage big data to identify specific market segments, understand their needs, and personalize messages for a higher chance of conversion.

3. Maximize Drip Marketing Efforts

Drip marketing is a strategy that involves sending subscribers a series of messages over time. It is effective because it:

• Actively engages leads and customers without overloading them with information
• Nurtures subscribers and keeps your brand top-of-mind
• Builds relationships and strengthens the bond between patients and healthcare providers
• Lets you customize the campaign depending on your goals (e.g., offer a new service or reactivate dormant leads)
• Reacts to user behavior, so you can always provide the right content at the right time

“Drip marketing structures vary according to your objectives, audiences, and length of the email campaign.” 

To show you an example of a sequence, let us say you are a dental clinic inviting old customers back after the pandemic.

Your email series may look like this:

• Email 1: Welcome back. This email informs your subscribers your clinic doors are open again. Include a FAQ section to let them know what to expect during the visit. Provide your schedule, and add a clear Book an Appointment call to action (CTA) on the page.
• Email 2: Incentives. Not everyone will immediately sign up to get their teeth cleaned. You can encourage them further by offering promos, discounts, and other incentives. Make these exclusive to email subscribers only.
• Email 3: Inspire them with new content. Do you want to bump your patient appointments? Share the latest dental news and tips. Emphasize why getting their dental health back on track is essential today.
• Email 4: Last-chance offer. If you still have not received a response from your subscribers, send them one last offer. This email should sound urgent to push people to book an appointment before it expires.
• Email 5: Appointment follow-up. Did they finally book a consultation? Send a follow-up message to thank them for coming in. You can include a short survey to get feedback about the experience.
• Email 6: Post-appointment follow-up. After the patient has left, send another email to thank them for their business. You can also invite them back for another cleaning in six months or a year.

4. Take Advantage of the Trends

“Healthcare marketing is changing rapidly. And you can harness these shifts to produce more compelling, audience-centric content.” 

These are some of the top healthcare marketing trends:

• Digital health tools. Brands are investing more in digital health platforms to reach and engage patients. These include telehealth, remote patient monitoring, and digital therapeutics. Meanwhile, marketers are using technologies such as cloud computing to speed up data collection and analysis.
• Consumer-driven healthcare. Patients are taking a more active role in their health and well-being. They are researching treatments and providers and making decisions based on their needs. In response, marketers should develop easily accessible and digestible content.
• Rise of social media. Social media is no longer an afterthought in healthcare marketing. It is a powerful platform to reach and engage patients, build relationships, and drive conversions. Use it to complement email marketing by adding social media buttons to your newsletters or inviting followers to subscribe to your mailing list.

5. Always Include the Basics

Email marketing basics are called such because they work regardless of the trends and changes in consumer behavior. In other words, they are non-negotiable.

Begin with the following tips:

• Spruce up your mailing list. Remove inactive contacts, update information, and add new subscribers. This way, you can reduce your bounce rate, create more targeted content, and increase click-through and conversion rates.
• Design a responsive email. Optimize your layout for small screens using a single-column template, large font sizes, and clear CTAs. You can also use accelerated mobile pages (AMPs) to create interactive and engaging emails without relying excessively on images.
• Perform split tests. A/B or split testing compares two or more email versions to see which performs better. It can be the subject line, CTA button color, email layout, etc. Conduct split tests for at least two weeks and monitor your results with Google Analytics or similar platforms.
• Utilize automation. Automated emails are sent without you having to lift a finger. They can be in the form of welcome messages, appointment reminders, post-purchase follow-ups, etc. Automated emails save you time and increase conversions because recipients get them at the right time.

Summing Up

Healthcare email marketing personalizes the brand experience, helping patients feel attended to and cared for. Executed well, it can also result in higher open rates, click-through rates, and returns.

These five ideas ensure you can launch a productive marketing campaign today. But if you want to amplify your efforts, working with a digital marketing agency specializing in your industry helps. You can count on the team to deeply understand your target market, know the latest trends, and utilize the most effective strategies.

Also, Read 7 Ways Machine Learning Can Enhance Marketing

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