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.
Datasets, registries and benchmarks you can train or evaluate oncology models on — with access conditions, licences, sizes, annotations and the models already using them. { } export JSON
HLA Ligand Atlas
A benign-tissue reference peptidome: the set you check a candidate neoantigen against to make sure healthy tissue does not present it too.
IEDB — Immune Epitope Database
The field's central repository of epitope data and the source of almost every training set for peptide–MHC models — and of their allele skew.
MHC Motif Atlas
The reference collection of HLA binding motifs — and the clearest picture of the field's long tail: a million measured ligands still describe barely 135 of thirty thousand alleles.
Mono-allelic HLA class I peptidome (Sarkizova / Abelin)
The engineered-cell peptidome that gave the field clean allele labels; fifteen of its alleles had no described motif before, and the panel covers at least one allele in 95% of people worldwide.
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.