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

Mirai

MIT Jameel Clinic / Massachusetts General Hospital · 2021

Task-specific model Open weights Research use only

Mammography-based model predicting five-year breast cancer risk from the four standard screening views, designed to be robust across hospitals and to work with or without clinical risk factors.

Risk prediction Screening Mammography

Invasive Breast Carcinoma

GitHub Paper Open card →

Sybil

MIT Jameel Clinic / Massachusetts General Hospital · 2023

Task-specific model Open weights Research use only

Deep-learning model that predicts an individual's risk of lung cancer over the next one to six years from a single low-dose chest CT, without radiologist annotations or clinical variables.

Risk prediction Screening CT

Lung & Bronchus

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.