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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM43375
Volume:
9 |
3 |
Mar 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Machine-Aided Diagnosis System is an intelligent healthcare solution designed to enhance diagnostic accuracy and accessibility through machine learning and AI-driven interactions. The system employs the Random Forest algorithm to analyze multiple symptom correlations, enabling precise disease prediction based on both general and chronic symptoms. An interactive disease dashboard provides a comprehensive symptom profile, suggested specialists, and available treatment methods, ensuring users can interpret their health conditions effectively. Additionally, an LLM( Large Language Model )-powered chatbot offers real-time conversations, assisting users with symptom explanations, treatment suggestions, and specialist recommendations. By integrating machine learning for prediction, interactive visualization for clarity, and AI-driven conversations for support, the system enhances user experience and medical accessibility. This innovative approach bridges the gap between advanced healthcare technology and everyday diagnostic needs, making disease prediction more intuitive and efficient.
KEYWORDS
Publication Date
3/30/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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