medicine suggestions system based machine learning

khushboo birjuchand uike; Dr. G.M. Vaidya; N.U. Sambhe

doi:10.36948/ijfmr.2026.v08i02.67824

medicine suggestions system based machine learning

Author(s)	Ms. khushboo birjuchand uike, Dr. G.M. Vaidya, N.U. Sambhe
Country	India
Abstract	Integrating technology in healthcare sector has not only made it easier but also has imparted better understanding of health problems which ultimately results into more healthy managing of health. The situation has gotten to such an extent that the west is combining the treatments of both the allopathic system and modern technology to provide the support that is not only easy to reach but also personalized. The initiative brings to the table a comprehensive Machine Learning-driven system for allopathic medicine and lifestyle recommendations which is largely based on symptoms. The computer examines the symptoms and the user's health data such as age, sex, allergies, and health history in order to use the SVC model to guess the diseases, which is specially trained on the allopathic datasets. The advanced algorithms are not only assisting in discerning the illness but also are suggesting to the users changes in their lifestyles and providing them with various modes of treatment that are specific to them. The prime purpose behind this strategy is to empower the consumers with the help of information and tools, which then leads to their health being improved and they becoming more proactive concerning their health. The system allocates the allopathic medicines, herbs, and lifestyle changes such as diet, yoga, and exercise, etc., based on the allopathic principles with the given disease as a factor. The system ensures that the recommendations are safe and relevant through the application of a rule-based sensitivities before making the recommendations. The user interface is meant to be a modern and user-friendly website. The backend is written in Python (Flask and Fast API are the frameworks used) and it takes care of data preprocessing, disease prediction, and drug recommendation logic. The application has a lot of potential especially in telemedicine services, holistic health applications, and patient support through self-care in regions with great reliance and practice of allopathic medicine.
Keywords	Allopathic Medicine, Machine Learning, Symptom Analysis, Personalized Healthcare, Disease Prediction, Support Vector Classification (SVC)
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-03-13
DOI	https://doi.org/10.36948/ijfmr.2026.v08i02.67824

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medicine suggestions system based machine learning

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