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Enter a patient's clinical measurements to estimate heart-disease risk.

Patient information

Enter raw clinical measurements. Optional measurements may be left blank — the model imputes missing values server-side.

Patient details

Basic demographic information.

Age

years

Sex

MaleFemale

Medical history

Symptoms and presentation.

Chest pain type

Fasting blood sugar > 120 mg/dL

YesNo

Exercise-induced angina

YesNo

Clinical & diagnostic measurements

From blood tests, ECG and exercise stress testing.

Resting blood pressure

mm Hg

Serum cholesterol

mg/dL

Maximum heart rate

bpm

ST depression (oldpeak)

Resting ECG result

ST segment slope

Major vessels (fluoroscopy)

Thallium test result

Raw values are sent exactly as entered. All imputation, encoding and scaling happens in the backend pipeline.

Backend status

Live status of the FastAPI inference service and the loaded model.

Checking the prediction service…

About this model

How the risk estimate is produced.

A Random Forest classifier, trained on the UCI heart-disease dataset (920 patients), is served by the FastAPI backend. The raw values you enter are imputed, encoded and scaled inside the serialized pipeline — none of that happens in the browser.