https://doi.org/10.1200/JCO.21.01337. A large external validation showing Mirai’s 1–5-year risk prediction held across seven health systems with C-indices ~0.75–0.84.
2. MIT Jameel Clinic. “Mirai.” Accessed October 2, 2025. https://jclinic.mit.edu/mirai/. Public page reporting Mirai’s scale (2M+ mammograms;72 hospitals;22 countries) and intended clinical use.
3. National Academy of Medicine. “Can AI Predict Breast Cancer? How a Scientist’s Personal Journey Led to an AI Model.” June 12, 2025. https://nam.edu/news-and-insights/can-ai-predict-breast-cancer/. Barzilay explains Mirai’s core idea—“the tissue itself imprints a lot of information.”
4. Mikhael, Peter G., et al. “Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk from a Single Low-Dose Chest CT.” Journal of Clinical Oncology 41, no.13 (2023): 2458–69. https://doi.org/10.1200/JCO.22.01345. Introduces Sybil and validates 1–6-year lung-cancer risk prediction.
5. UC Davis Health. “New AI Technology Helps Physicians Quickly Identify Stroke.” February 1, 2024. https://health.ucdavis.edu/news/headlines/new-ai-technology-helps-physicians-quickly-identify-stroke/2024/02. Local rollout with Dr. Kwan Ng’s quotes on prioritization and speed.
6. U.S. Food and Drug Administration. “IDx-DR — DEN180001: Decision Summary.” 2018. https://www.accessdata.fda.gov/cdrh_docs/reviews/DEN180001.pdf. FDA’s official De Novo review for the first autonomous diagnostic AI.
7. Repici, Alessandro, et al. “Efficacy of Real-Time Computer-Aided Detection During Colonoscopy.” Gastroenterology 159, no.2 (2020): 512–20.e7. https://doi.org/10.1053/j.gastro.2020.04.062. Multicenter RCT showing adenoma detection rate gains with CADe.
8. U.S. Food and Drug Administration. “Paige Prostate — De Novo Decision Letter (DEN200080).” September 21, 2021. https://www.accessdata.fda.gov/cdrh_docs/pdf20/DEN200080.pdf. FDA authorization for the first AI tool in diagnostic pathology.
9. Wong, Andrew, et al. “External Validation of a Widely Implemented Sepsis Prediction Model.” JAMA Internal Medicine 181, no.8 (2021): 1065–70. https://doi.org/10.1001/jamainternmed.2021.2626. Shows Epic’s sepsis model performed poorly in real-world testing.
10. Obermeyer, Ziad, Brian Powers, Christine Vogeli, and Sendhil Mullainathan. “Dissecting Racial Bias in an Algorithm Used to Manage the Health of Populations.” Science 366, no. 6464 (2019): 447–53. https://doi.org/10.1126/science.aax2342. Demonstrates bias when cost is used as a proxy for health need.
11. Garde, Damian. “IBM’s Watson Recommended ‘Unsafe and Incorrect’ Cancer Treatments.” STAT, July 25, 2018. https://www.statnews.com/2018/07/25/ibm-watson-recommended-unsafe-incorrect-treatments/. Reporting on internal documents detailing Watson for Oncology’s failures.