International Journal of Computer Techniques Volume 12 Issue 3 | AI-Based Health Disease Detection and Risk Prediction System
AI-Based Health Disease Detection and Risk Prediction System
International Journal of Computer Techniques – Volume 12 Issue 3, May – June – 2025
Abstract
AI-driven predictive disease modeling aids early diagnosis and risk assessment. This paper examines Machine Learning algorithms such as Random Forest, SVM, Decision Trees, and Gradient Boosting for healthcare analytics.
Keywords
Disease prediction, AI in healthcare, Random Forest, SVM, Machine Learning, Decision Tree, Gradient Boosting.
Conclusion
The AI-based health prediction system achieves up to 95% accuracy in early disease detection. Ensemble learning and optimization strategies further enhance model precision.
References
- Haque, M., Kabir, M., & Adnan, R. (2024). Multi-class heart disease detection using Machine Learning. arXiv.
- Yi, J., Cheng, H., & Wang, J. (2024). Transformer-based heart disease prediction model optimization. ICCAE.
- Ingole, B. S., & Chavan, P. N. (2024). Advancements in AI-driven disease risk assessment. IJERT.
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