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

Task Data type Cancer Clinical setting Availability Regulatory status Kind Search Sort × Clear filters

CHIEF

Yu Lab, Harvard Medical School · 2024

Foundation model Open weights Research use only

Clinical Histopathology Imaging Evaluation Foundation model: trained on 60,530 whole-slide images across 19 anatomical sites and validated on 19,491 slides from 24 hospitals for cancer detection, tumour-origin prediction, genomic profiling and survival.

Feature extraction (embeddings)Classification Prognosis Survival analysis Histopathology (WSI)

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.