MediScan – Health Risk Guidance System
A machine learning-based healthcare system that predicts diseases from user symptoms and provides actionable guidance including severity analysis, precautions, and nearby hospital recommendations.
A machine learning-based healthcare system that predicts diseases from user symptoms and provides actionable guidance including severity analysis, precautions, and nearby hospital recommendations.
Most symptom-based systems provide limited or vague predictions without actionable guidance, leaving users uncertain about next steps or severity of their condition.
Built a system that predicts diseases and enhances the output with severity levels, precautions, and real-world recommendations to help users make informed decisions.
Built a multi-class classification model trained on symptom-disease relationships to predict the most likely conditions.
Synthetic healthcare dataset (IBM), enabling fast prototyping and controlled experimentation.
Achieved high accuracy (~99%) due to synthetic dataset. Real-world performance may vary, and future work includes training on real clinical datasets for improved generalization.