CareGenie: A machine learning Based Medical Recommendation System for Symptom Analysis and Personalized Health Guidance

Author(s)	Mr. Harsh Kumar Singh, Mr. Rahul Tripathi, Mr. Rohit Pandey, Dr. Sharanabasava Inamadar
Country	India
Abstract	CareGenie is an explainable AI system addressing critical global healthcare challenges—clinician shortages, diagnostic delays, and rising chronic diseases. Combining a Gradient-Boosted Decision Tree with a rules-based engine, it delivers 94.7% accurate disease predictions and personalized health guidance. Trained on 8,192 symptom-disease pairs from Indian health datasets, it uses SHAP for interpretability and incorporates Ayurvedic principles. A 12-week pilot at DPU Hospital (N=214) cut unnecessary ER visits by 31%, with 89% user satisfaction (N=142). Its modular, HIPAA-compliant architecture makes it scalable for low- and middle-income countries.
Keywords	Explainable AI, Decision Trees, Preventive Healthcare, Telemedicine, WHO Sustainable Development Goals.
Field	Engineering
Published In	Volume 7, Issue 3, May-June 2025
Published On	2025-05-15
DOI	https://doi.org/10.36948/ijfmr.2025.v07i03.44613
Short DOI	https://doi.org/g9kfqb

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