dc.contributor.author | Kouser, Nashid![]() |
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dc.contributor.author | Barekzai, Sara![]() |
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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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