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Comparative Analysis of Medication Based on Machine Learning Models

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dc.contributor.author Kouser, Nashid
dc.contributor.author Barekzai, Sara
dc.date.accessioned 2022-01-19T18:49:46Z
dc.date.available 2022-01-19T18:49:46Z
dc.date.issued 2021-04-28
dc.identifier.uri http://hdl.handle.net/1920/12204
dc.description.abstract Our society is seeing a sharp rise in the number of people suffering from complicated chronic diseases. Presently, 6 in 10 adults in the United States have a chronic disease. This is the leading cause of death and the leading driver of the Nation's $3.8 Trillion in Annual Health Care Costs. With that figure predicted to grow, clearly, something is lacking from the one-size. the fits-all paradigm of traditional medicine. Caring for this new population requires an entirely different mindset; this is where functional medicine steps in. Functional medication can help prevent disease thus potentially proving to be more cost-effective for the insured and insurer overall in the long term. However, there are approximately 1400 functional medicine practitioners across the U.S., and a little under 350 that accept insurance. We analyze health data from a new point in this research. en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject artificial intelligence en_US
dc.subject medication en_US
dc.subject homeopathy en_US
dc.title Comparative Analysis of Medication Based on Machine Learning Models en_US
dc.type Working Paper en_US


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