About

Why this exists

AI-based diagnostics in oncology are entering U.S. clinical practice at a rapid pace, but the field lacks a single curated reference. Researchers, clinicians, regulators, payers, and journalists currently piece together the landscape from FDA databases, individual press releases, and company websites — a slow process that often produces inconsistent counts and out-of-date information.

The OncologyAI Registry is a public, open-data resource that consolidates this information using consistent inclusion criteria, source-citation standards, and a quarterly refresh cycle.

Curator

The registry is curated by Ahmed Elbakri, an immigrant healthcare AI leader with operational and regulatory expertise in deploying AI-powered diagnostics in U.S. oncology. Ahmed leads laboratory operations and regulatory strategy at Valar Labs (a16z, DCVC-backed), where he architected the FDA Breakthrough Device-designated Vesta bladder cancer assay. He holds an MBA from Stanford and previously co-founded Yocto Biosciences. He is independently named as a collaborator on Baylor College of Medicine AI oncology research grants.

Independence and conflict-of-interest

The registry is operated independently. While the curator is employed by one of the listed companies, that company's products are evaluated under the identical inclusion criteria and source-citation standards as every other entry. The curator holds no equity, advisory, or compensation relationships with any other listed company. The full disclosure statement is available in the Methodology.

Contact

Issues, contributions, and corrections: please use the GitHub repository (link in the header). Press inquiries and partnership questions: contact via the curator's professional email listed on the GitHub README.