AI-POWERED HEALTHCARE DIAGNOSIS SYSTEM: A SYMPTOM- BASED PREDICTION APPROACH

Author(s)	Dr. Vijay Kumar Samyal, Mr. Prahlad Kumar, Mr. Deepak Kumar
Country	India
Abstract	AI-powered systems are becoming increasingly important in healthcare for early disease detection. Many patients face difficulty understanding their symptoms, which leads to delayed diagnosis. This research focuses on building a symptom-based disease prediction system using machine learning. A publicly available symptom–disease dataset is used, which contains symptoms, severity levels, disease descriptions and precautions. Two machine learning models, Random Forest and XGBoost, are trained and evaluated using accuracy, precision, recall, and F1-score. The results show that XGBoost performs slightly better due to its boosting technique and ability to handle complex symptom patterns. The system can help users and healthcare workers in quick preliminary diagnosis and decision support.
Keywords	AI in Healthcare, Symptom-based Diagnosis, Machine Learning, Random Forest, XGBoost, Disease Prediction
Field	Engineering
Published In	Volume 16, Issue 4, October-December 2025
Published On	2025-12-14
DOI	https://doi.org/10.71097/IJSAT.v16.i4.9875
Short DOI	https://doi.org/hbf822

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International Journal on Science and Technology