🏥 HealthLens AI

• HealthLens AI is a AI-Integrated smart healthcare assistant designed to simplify complex medical reports and to improve early disease awareness.

• It predicts disease risks using basic health parameters such as age, BMI, blood pressure, blood sugar, and lifestyle habits.

• The system displays moderate and high risk of having a disease along with the percentage possibility of having a disease.

• Additionaly, it simplifies complex medical reports into clear and understandable language for non medical users

• This provides a fast, accessible, and user-friendly alternative to existing complex healthcare systems

  

💡 Don’t have a medical report? Use the sample medical report below to test the app.

Medical Examination Report 

Patient Name: John Doe  
Age/Sex: 45/M  
Date: 12-03-2026  
Ref No: HL-2026-0312-045  

Chief Complaints:
Patient presents with complaints of intermittent chest discomfort over the past 2 weeks, associated with generalized fatigue and occasional episodes of lightheadedness. No history of syncope.

Past Medical History:
- No known history of diabetes mellitus
- Borderline hypertension noted 1 year ago
- Family history significant for coronary artery disease (father)

Vital Parameters:
BP: 142/92 mmHg  
Pulse: 94 bpm (regular)  
Respiratory Rate: 18/min  
Temperature: Afebrile  

Laboratory Investigations:

Complete Blood Count (CBC):
Hemoglobin: 13.2 g/dL  
WBC Count: 7,800 /mm³  
Platelets: 2.5 lakh /mm³  

Biochemistry:
Fasting Blood Glucose: 134 mg/dL  
Postprandial Blood Glucose: 178 mg/dL  
HbA1c: 6.8%  

Lipid Profile:
Total Cholesterol: 248 mg/dL  
Triglycerides: 210 mg/dL  
LDL Cholesterol: 162 mg/dL  
HDL Cholesterol: 36 mg/dL  

Renal Function:
Serum Creatinine: 1.1 mg/dL  
Blood Urea: 32 mg/dL  

ECG Findings:
Normal sinus rhythm with occasional premature ventricular contractions (PVCs). No acute ST-T changes.

Clinical Impression:
Findings suggest borderline uncontrolled hypertension with dyslipidemia and impaired glucose tolerance. Patient exhibits risk factors for atherosclerotic cardiovascular disease.

Medications Prescribed:
- Tab. Amlodipine 5 mg once daily (for blood pressure control)  
- Tab. Atorvastatin 10 mg once daily at bedtime (for cholesterol management)  
- Tab. Metformin 500 mg once daily after meals (for glucose control)  
- Tab. Aspirin (Ecosprin) 75 mg once daily (antiplatelet therapy)

Advice:
Further evaluation with echocardiography and stress test recommended. Lifestyle modification advised. Pharmacological intervention may be considered based on follow-up.

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Note: This is a simulated medical report generated for testing and demonstration purposes only.

🚀 Key Features

🔮 1. Disease Risk Prediction System

HealthLens AI analyzes user health parameters and predicts the risk level of potential diseases.

✅ Input Parameters:

• Age

• Body Mass Index (BMI)

• Blood Pressure

• Blood Sugar Levels

• Smoking

• Physical Activity Level

⚙️ How it Works:

Uses a rule-based system for fast and reliable predictions

Identifies moderate and high-risk diseases

📊 Output:

Displays disease risk level (Moderate / High)

Provides percentage probability of risk

If all values are normal:

• ✅ Displays a “You are in good health” message

📄 2. Medical Report Simplifier (AI-Powered)

This is the key highlight of the project 💡

Users can either:

• Paste medical report text (or)

• Upload a medical report (PDF/text)

🤖 Powered by:

Gemini AI API

⚙️ How it Works:

The system:

• Reads the medical report

• Converts it into simple, understandable language

• Identifies and explains complex medical terms

• Extracts and explains medications (if present):

  • What the medicine is

  • Why it is used

  • When to take it

🧾 Output Includes:

• Simplified summary of the report

• Explanation of medical terms

• Medication guidance

• Personalized health suggestions

Our system identifies key clinical terms and translates them into insights for non-medical users.

🧠 Innovation

Combines rule-based prediction + AI-powered report simplification

Focuses on accessibility for non-medical users

Reduces dependency on medical expertise for basic understanding

🛠️ Tech Stack

💻 Frontend:

HTML

CSS

JavaScript (Custom UI)

⚙️ Backend:

Python

Flask (Handles application logic and routing)

📊 Prediction System:

Rule-based logic for disease risk analysis

🤖 AI Integration:

Gemini AI via Gemini API (for report simplification)

⚙️ WorkFlow of HealthLens AI

1. User enters health data or uploads report

2. Data is sent to Flask backend

3. Based on input:

• Rule-based engine → Disease prediction

• Gemini AI → Report simplification

4. Results are processed and displayed

5. User receives clear and actionable insights

🚀 Future Enhancements

Integration of Machine Learning models using real-world datasets

Improved prediction accuracy using trained models

Support for more diseases and reports

Multi-language support for wider accessibility

📌 Conclusion

HealthLens AI bridges the gap between complex medical data and user understanding by combining intelligent prediction with AI-powered simplification.

It empowers users to take early and informed health decisions — making healthcare more accessible, understandable, and proactive.