Medical AI · Visual question answering

Ask a question about a radiology image

MediQNet looks at a medical image, reads your question, and answers it. It handles the four kinds of question in the ImageCLEF VQA-Med 2019 benchmark: imaging modality, plane, organ system and abnormality. The neural network runs entirely in your browser; images never leave your device.

1 · Pick an image

Test images from VQA-Med 2019 that the model never saw during training, or upload your own.

Selected radiology image

2 · Ask a question

Answer

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Research demo only. Not for diagnosis or any clinical use.

How well it answers

Exact-match accuracy on the official VQA-Med 2019 test set (500 questions, 125 per category), next to the challenge's best team.

How it works

A compact version of the MediQNet design (originally BioBERT + Swin Transformer), sized to run on a phone: the image and the question are encoded separately, fused, and classified over every answer seen in training. The question's category, detected from its wording, limits which answers are allowed.

Radiology image224 × 224 RGB MobileNetV3-Largefine-tuned · 960-d features Question"what plane is this?" Bag of words → 128-d+ category detector Fusion MLP1,088 → 512 → answers Answerlimited to the question's category