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AI in Oncology · AI Models

A researcher-grade catalog of AI models, datasets and open data needs in oncology — every card structured, sourced and dated.

Filter by task, data type, cancer, availability and regulatory status. Each card follows one model-card standard and links to Hugging Face, code, papers and the datasets it was trained or tested on. { } export JSON

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1 / 35 models Tick 2–4 models to compare them side by side.

nnU-Net v2

German Cancer Research Center (DKFZ), Division of Medical Image Computing · 2020
Framework Open weights Not applicable

Self-configuring segmentation framework: given a labelled dataset it chooses preprocessing, network topology and training schedule automatically, and it remains the baseline to beat on most medical segmentation challenges, including tumour tasks.

Segmentation CTMRIPET
Pan-cancer
GitHub Paper Open card →

Cards follow the cancer3.ai model-card standard: AI_MODEL_CARD_STANDARD.md. Corrections and new entries: contact the editorial team; every fact needs a public source.

This page is educational — it is not medical advice and does not replace consultation with an oncologist. Diagnostic and treatment decisions are made solely by specialist physicians.