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The goal of the medication recommendation system is to prescribe different medications based on the cosine similarity between a patient's symptoms and the effects of different drugs. The system uses a list of potential patient symptoms as well as a database of drugs and their indications. It applies filters, vectorizes the data, and generates recommendations. Patients are advised to take medications that have a higher cosine similarity because they are deemed more pertinent. This recommender is a useful tool in the event of a medical emergency when doctors or prescribed drugs are not available. The suggested drug recommendation system may be able to assist patients and medical professionals in selecting complementary medicines with knowledge. The method can lessen the possibility of negative medication reactions and enhance.
Keywords:
Alternative Medicine, Cosine Similarity, Medicine Recommendation System, Patient Symptoms, Drug Effects.
Cite Article:
"Alternative Medicine Recommendation System using Machine Learning", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 2, page no.241 - 246, February-2024, Available :http://www.ijrti.org/papers/IJRTI2402037.pdf
Downloads:
000205132
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator