Un médecin qui utilise l'IA

This AI makes it possible to assess the progression of chronic diseases

Researchers from the University of Buffalo have developed a new system based on artificial intelligence. This device makes it possible to model the progression of chronic diseases as patients get older. This AI model analyzes metabolic and cardiovascular biomarkers to determine a patient’s health. This technology can also assess disease risks that could affect him throughout his life.

Scientists have said that as they age, individuals have an increased risk of developing chronic and cardiovascular diseases. According to a pharmaceutical scientist, there is an unmet need for scalable approaches. These approaches have the potential to provide useful tips for pharmaceutical care.

The American Heart Association further clarified that cardiovascular disease can be linked to several conditions. These include heart disease, heart attacks, stroke, heart failure, arrhythmia, and heart valve problems.

In the United States, a person dies of heart disease every 36 seconds

Heart disease kills a person, says Centers for Disease Control and Prevention every 36 seconds in the United States. You should also know that approximately 659,000 Americans die of this condition every year.

The model could then assess the risks associated with long-term chronic drug treatments. It also allows clinicians to monitor responses to care for conditions such as diabetes, high cholesterol and high blood pressure.

Almost 40,000 people in the United States have been screened

The team of American researchers used data from three case studies. These are part of the third national survey on health and nutrition (NHANES). In fact, these reviews made it possible to assess the metabolic and cardiovascular biomarkers of nearly 40,000 people in the USA.

For information, biomarkers include measures such as temperature, body weight, and height. Note that these elements are useful for diagnosing, treating and monitoring overall health and myriad diseases.

The research was conducted by Mason McComb, UB School of Pharmacy and Pharmaceutical Sciences, Rachael Hageman Blair, Associate Professor of Biostatistics at UB School of Public Health and Helth Professions and Martin Lysy, Associate Professor of statistics and actuarial science at the University of Waterloo.

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