AI-Driven Personalized Medical Recommendation System

Faizan Ahmad; Mansi Soni; Nigar Parveen; Saurabh Kumar Upadhyay; Syed Kazeem Akbar

doi:10.55524/ijircst.2025.13.3.5

Abstract

The advancement of Artificial Intelligence (AI) has paved the manner for wise healthcare solutions that may beautify prognosis and treatment hints. This paper provides an AI-driven Personalized Medical Recommendation System, which predicts diseases primarily based on person-input signs and indicates relevant drugs. The system leverages machine learning algorithms using supervised studying techniques for sickness prediction and content-primarily based filtering for medication guidelines. A Flask-based web application ensures accessibility, providing real-time interaction. Experimental effects suggest that the system provides exceptionally accurate and reliable clinical recommendations, showcasing the capacity of AI in modern healthcare. The development of a Medicine Recommendation System ambitions to help healthcare specialists and sufferers in selecting appropriate medications based totally on individual clinical profiles and particular situations.

Keywords

Medical Recommendation System, Machine Learning, Personalized Healthcare, AI in Healthcare, Healthcare Informatics, Symptom-Based Diagnosis, Disease Prediction, AI in Medicines, Clinical Decision Support, Personalized Treatment Plans, AI-Driven Healthcare Solutions.

References

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Cites this article as

F. Ahmad, M. Soni, N. Parveen, S. K. Upadhyay, S. K. Akbar, "AI-Driven Personalized Medical Recommendation System", International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-13, Issue-3, Page No-26-34, 2025. Available from: https://doi.org/10.55524/ijircst.2025.13.3.5

Corresponding Author

Nigar Parveen

B.Tech Scholar, Computer Science and Engineering , Integral University , Lucknow , India

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