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Artificial intelligence and machine learning have been utilized for years in the field of healthcare and continue to grow tremendously each year with its ability to advance medicine and discoveries in the industry.
The term precision medicine, sometimes referred to as personalized medicine, is a relatively new term in the healthcare field but the idea has been around for many years in the industry. According to the U.S. National Library of Medicine, precision medicine is "an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person."
Precision medicine helps physicians determine more personalized treatments for patients considering individualized approaches instead of a blanketed approach for all patients. They do this by looking at a patients genetic history, location, environmental factors, lifestyle and habits to determine a plan of action for treatment.
With artificial intelligence, it takes precision medicine to the next level and increases the accuracy and prediction of outcome for patients. Some actually believe that precision medicine is not completely possible without the addition of machine learning algorithms to assist in the process.
In a report from Chilmark Research, it states that to achieve the full potential of precision medicine it must be accompanied by machine learning and artificial intelligence due to the deep learning technology and ability to analyze large data sets faster than clinicians and medical researchers.
Not only can AI read and analyze large sets of medical data much faster than a human, it can more accurately determine results to come to conclusions about a patients treatment options and possible outcomes of the treatment.
With AI, the ability to not only predict outcomes but also be able to predict future patients probability of having diseases is a major benefit for precision medicine. By better understanding why diseases may occur and in what environments they are more likely to occur, artificial intelligence can help in the education of medical professionals to know what to look for before a disease is showing symptoms. To be able to evaluate the risk of disease in patient populations is revolutionary for healthcare and the lives of many.
Machine learning can also help improve FDA regulations of tests, drugs and pharmaceutical partnerships to help support treatments. Fully achieving precision medicine effectively takes a collaboration of pharmaceutical companies, biotechs, academia, diagnostic companies and others to drive innovation forward.
Amplion, a leading precision medicine intelligence company, recently released Dx:Revenue, a software intelligence platform that uses machine learning to deliver insights into pharmaceutical partnerships.
The platform uses over 34 million data sources from clinical trials, scientific publications, conference abstracts, FDA approved tests, lab tests, and other information to match a test providers capabilities to pharmas specific needs.
This is particularly important in cancer, where were moving away from the one-size-fits-all approach to care toward a more targeted approach with treatments based on the biological characteristics of each patient, said CEO of Amplion Chris Capdevlia. Personalizing our approach to healthcare in this way not only results in better outcomes for patients, it also drives down drug development costs through shorter, more successful trials and reduces time to market for valuable drugs all very good news for better patient outcomes.
Precision medicine can truly improve the lives, and even save the lives, of many people and the use of artificial intelligence can increase those outcomes drastically. It can also make treatments more affordable and accessible to those who may not be able to receive those treatments due to cost and health insurance at this time. There are many challenges ahead for precision medicine to be perfect, but artificial intelligence can help drive us closer to those goals.
See more here:
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