Toward AI-Powered Cancer Etiology Research
Advances in multimodal longitudinal data and artificial intelligence (AI) create new opportunities for cancer etiology research. We envision an AI-powered discovery workflow integrating an interoperable epidemiologic data ecosystem and causal inference frameworks to accelerate the identification of both cancer causes and the converging biological states for prevention.
Authors
- George Hripcsak (ORCID: https://orcid.org/0000-0003-2664-7614)
- Jason D. Buenrostro (ORCID: https://orcid.org/0000-0001-9958-3987)
- Marinka Žitnik (ORCID: https://orcid.org/0000-0001-8530-7228)
- Linying Zhang
- Mengmeng Ji (ORCID: https://orcid.org/0000-0002-1205-0369)
Institutions
- Broad Institute (US)
- Harvard University (US)
- Washington University in St. Louis (US)
- Columbia University Irving Medical Center (US)
- Harvard Stem Cell Institute (US)
Publication Details
- Journal
- Cancer Discovery
- Published
- 2026-04-13
- DOI
- https://doi.org/10.1158/2159-8290.cd-25-2098
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00