← all systems · case file 04 · screen_risk() · Live on HF Spaces · Zenodo Preprint

PredictLab

Screening results that explain themselves

scikit-learn
FastAPI
Llama 3.1 (Groq)
Docker
Hugging Face Spaces

Summary

A containerized full-stack clinical risk screening platform on Hugging Face Spaces Three scikit-learn classifiers screen for diabetes stroke and heart disease across 30 clinical inputs and Llama 3.1 8B on Groq explains each result in accessible language Published as a research preprint on Zenodo in May 20261Live demo on Hugging FaceInteractive Demo · huggingface.co

What the sources say with how each number was obtained
Value	What	Method	Source
3	Clinical screening models	An SVM (diabetes) a Random Forest (stroke) and a Logistic Regression (heart disease) each a scikit-learn pipeline behind one FastAPI service	[2] repo
30	Health inputs analysed	Input fields across the three screening forms: 8 + 10 + 12	[2] repo
Preprint	Published on Zenodo May 2026	Zenodo record v1.0 17 May 2026 A preprint not peer-reviewed	[3] doi

Problem

A bare 'Diabetic / Not diabetic' output raises more questions than it answers for anyone without a medical or machine-learning background1Live demo on Hugging FaceInteractive Demo · huggingface.co

Architecture

SVM Random Forest and Logistic Regression behind one FastAPI service; Llama 3.1 explains each result

Three disease models
An SVM for diabetes a Random Forest for stroke and Logistic Regression for heart disease each in its own scikit-learn pipeline
One FastAPI service
A single FastAPI backend serves the web interface the prediction endpoints and the AI assistant with no frontend build step containerized with Docker
Contextual explanations
Patient inputs and model outputs go to Llama 3.1 8B on Groq which explains the result in plain language and answers follow-up questions

PredictLab: silent screen recording of the product in use.

Not claimed

Can it diagnose me?: No source says it diagnoses anything so I won't say it does It's a screening tool that explains risk For a diagnosis see a doctor