Methodology

Version 0.1 — last updated April 20, 2026

Purpose

The OncologyAI Registry exists to provide a single, curated, source-cited reference for AI/ML-based diagnostic tools available or in late-stage development for U.S. oncology. The registry is independent, open-data (CC BY 4.0), and updated quarterly.

Inclusion criteria

• The product uses an AI or machine-learning algorithm as a core component of clinical decision support, diagnosis, prognosis, or treatment selection.
• The intended clinical use is in oncology (any cancer type, any modality).
• The product is available, in clinical trial, or formally announced for the U.S. market — including Laboratory-Developed Tests (LDTs), FDA-cleared/approved devices, and Breakthrough Device-designated products.
• Each entry is supported by at least one verifiable public source (FDA database, peer-reviewed publication, or company-issued press release).

Exclusion criteria

• Pure research-only tools without a stated clinical translation pathway.
• Algorithms embedded in non-oncology workflows (e.g., AI for general radiology triage that doesn't specifically address oncology).
• Unsourced claims or products mentioned only in non-attributable secondary coverage.

Data fields

Each entry captures the following, where verifiable:

• Product name and company
• Cancer type(s) and modality (histopathology, radiology, genomic, liquid biopsy, multi-omics)
• Intended use as stated by the manufacturer or in the FDA labeling
• Regulatory status: FDA pathway (510(k), De Novo, PMA, Breakthrough Device, LDT), decision date, NY CLEP status, CLIA/CAP accreditation
• Clinical evidence: pivotal peer-reviewed publication(s) with PMID where available
• Deployment: market availability, partner labs, estimated cancer-center adoption
• Reimbursement: CPT / PLA codes, payer coverage notes (where public)
• Sources: every claim is linked to a verifiable URL with date accessed

Source hierarchy

When a fact is supported by multiple sources, we prioritize:

1. U.S. federal database entries (FDA 510(k), De Novo, PMA, Breakthrough Devices, ClinicalTrials.gov)
2. Peer-reviewed publications (PubMed-indexed)
3. Manufacturer regulatory documentation (FDA submissions, labeling)
4. Company-issued press releases attributable to a named source
5. Major trade press (STAT, Endpoints, MedTech Dive, BusinessWire)

Performance metrics are reported only from peer-reviewed publications, never from press releases or marketing materials.

Refresh cycle

The registry is reviewed quarterly. Material updates (new FDA decisions, major partnerships, or significant publications) are applied within two weeks of public availability.

Conflict-of-interest disclosure

The curator (Ahmed Elbakri) is currently employed by Valar Labs. Valar Labs products are listed in the registry under the same inclusion criteria and source-citation standards as every other entry. The curator has no equity, advisory, or compensation relationships with any other listed company. Disclosures are reviewed and republished with each quarterly update.

Citation

Please cite the registry as:

Elbakri A. OncologyAI Registry [v0.1]. Available at: https://oncologyairegistry.org. Accessed [date].

A formal methods paper describing the registry is in preparation and will be the canonical citation upon publication.

Contributing

Suggestions, corrections, and new-entry submissions are welcome via GitHub pull request. Each contribution must include a verifiable source URL and meet the inclusion criteria above.