Final Year Project — Computer Science

Intelligent Healthcare
Symptom Analysis System

Accurate, timely diagnosis is hard to get in regions with limited medical infrastructure. IntelliHealthcare analyzes patient-reported symptoms with a trained classification model and separately screens clinical report values for heart disease risk — giving doctors and patients a fast, structured second opinion instead of a guess.

intellihealthcare.vercel.app/disease-detector
Symptom Tracker
Fever Cough Headache Fatigue Nausea Chest Pain
Predict Disease
Self-care
Flu
Model confidence 96%
15
Conditions covered by the symptom classifier
2
Detection modules — Symptom Tracker & Heart Disease Detector
<2s
Average prediction response time
System pipeline

From symptoms to a structured result

1. Input collection

The patient selects reported symptoms from a curated list, or enters clinical values (BP, cholesterol, ECG) for the heart module.

2. Model inference

A Decision Tree classifier maps the symptom vector to a condition; a Random Forest classifier scores heart disease risk from the clinical inputs.

3. Guided output

Results are returned with an urgency label (emergency / see a doctor / self-care) so the next step is always clear.

IntelliHealthcare Assistant
Hi! I'm your health guidance assistant. Ask me about a symptom or condition — I'll share general advice (not a diagnosis).