• Sharique Shaikh
• Prof. Junaid Mandviwala
• Raza Shaikh
• Zoeb Ali Khan
• Tabish Sayyed

The Patient Diagnosis and Drug Recommendation System represents a cutting-edge application of advanced computational techniques in healthcare, designed to provide efficient decision support for healthcare professionals. By leveraging technologies such as natural language processing (NLP), extract-transform-load (ETL) pipelines, and random forest models trained on extensive medical data, the system aims to accurately detect and diagnose six major diseases: acne, ADHD, depression, type 2 diabetes, migraine, and pneumonia. This comprehensive approach addresses the growing need for innovative solutions to enhance diagnostic accuracy and streamline treatment recommendations in clinical practice. It holds the potential to revolutionize clinical decision-making by providing healthcare professionals with efficient and accurate tools for disease detection and treatment recommendation. By leveraging advanced computational techniques, the system aims to enhance diagnostic accuracy, optimize treatment pathways, and ultimately improve patient outcomes across a range of medical conditions. Through continuous refinement and integration with clinical workflows, the system seeks to empower healthcare professionals with the insights and resources needed to deliver personalized and effective patient care.

drug recommendation system, natural language processing, extract transform load

"DRUG DISCOVER: A RECOMMENDER SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.k545-k548, April-2024, Available :http://www.jetir.org/papers/JETIR2404A74.pdf

"DRUG DISCOVER: A RECOMMENDER SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppk545-k548, April-2024, Available at : http://www.jetir.org/papers/JETIR2404A74.pdf