• Chaitanya Krishna Suryadevara Softtware Engineer, Department of Computer Science


Machine learning, medicine recommendation, disease prediction, patient monitoring


The rapid advancements in healthcare technologies and the increasing availability of patient data have paved the way for the development of intelligent medication recommendation systems. These systems leverage the power of artificial intelligence and machine learning to provide personalized medication recommendations, thereby improving treatment outcomes and patient well-being. This research paper explores the design, development, and evaluation of such a system, emphasizing its ability to harness patient-specific information, medical knowledge, and historical treatment data to generate tailored medication recommendations. The proposed system employs sophisticated algorithms to analyze patient profiles, medical histories, and relevant clinical guidelines to offer evidence-based and patient-centered medication suggestions. Through a comprehensive review of existing research, we present the state-of-the-art in intelligent medication recommendation systems and highlight the challenges and opportunities in this burgeoning field. We also discuss the ethical and privacy considerations associated with deploying such systems in healthcare settings. The outcomes of this research are expected to contribute significantly to the advancement of personalized medicine and enhance the quality of care delivered to patients worldwide.


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How to Cite

Chaitanya Krishna Suryadevara, “TOWARDS PERSONALIZED HEALTHCARE - AN INTELLIGENT MEDICATION RECOMMENDATION SYSTEM”, IEJRD - International Multidisciplinary Journal, vol. 5, no. 9, p. 16, Dec. 2020.