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

BiomedBERT (PubMedBERT)

Microsoft Research · 2020

Foundation model Open weights Not applicable

BERT pretrained from scratch on PubMed abstracts and PMC full text with a biomedical vocabulary; the workhorse encoder for named-entity recognition, relation extraction and classification over oncology literature and reports.

Information extraction Classification Feature extraction (embeddings) Biomedical literature Clinical text

Pan-cancer

🤗 220 044 downloads / month ♥ 335 updated 2023-11-06 Hugging Face Paper Open card →

TrialGPT

NIH National Library of Medicine (with National Cancer Institute collaborators) · 2024

Tool API / hosted only Research use only

Three-stage LLM framework (retrieval, criterion-level matching, ranking) that matches a patient summary to clinical trials from ClinicalTrials.gov; in the paper it cut clinician screening time by more than 40% in a pilot user study.

Clinical-trial matching Information extraction Clinical text

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.