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A newer version of the Gradio SDK is available: 6.24.0

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metadata 
title: MoPET Medical Classification
emoji: 🩺
colorFrom: gray
colorTo: pink
sdk: gradio
sdk_version: 6.22.0
app_file: app.py
short_description: MoPET mixture-of-experts medical image classification
python_version: '3.12'
startup_duration_timeout: 30m

MoPET Medical Classification

This Space demos MoPET: Parameter-Efficient Mixture-of-Experts for Unified Medical Image Classification (EMA4MICCAI 2026 Workshop).

MoPET adapts a frozen DINOv3 ViT-B/16 backbone with a learned sparse top-k router over a heterogeneous pool of LoRA + BOFT PEFT experts injected into the attention qkv projections. A single model consolidates four MedMNIST+ classification tasks (Blood, Breast, Derma, Path) behind one shared, sparsely-routed expert pool.

Usage

  1. Upload a medical image (blood cell microscopy, breast ultrasound, dermoscopy, or colon pathology histology).
  2. Select the matching task head.
  3. Click Classify to get per-class probabilities.

Disclaimer: This is a research artifact, not a diagnostic device. Outputs must not be used for clinical diagnosis.

Links