'Image based cancer risk models' - Jacob Silterra - AICamp Boston August Meetup

Talk by machine learning engineer Jacob Silterra on the Sybil lung cancer risk model and the Mirai breast cancer risk model developed at the MIT Jameel Clinic (in collaborations with Massachusetts General Hospital and others). Minor correction: at 9:26, 20/1000 is quoted as 0.2%, should be 2%.

References:

Yala, Adam, Peter G. Mikhael, Fredrik Strand, Gigin Lin, Kevin Smith,
Yung-Liang Wan, Leslie Lamb, Kevin Hughes, Constance Lehman, and
Regina Barzilay. “Toward Robust Mammography-Based Models for Breast
Cancer Risk.” Science Translational Medicine 13, no. 578 (January 27,

“Multi-Institutional Validation of a Mammography-Based Breast Cancer
Risk Model | Journal of Clinical Oncology.” Accessed July 26, 2024.

Mikhael, Peter G., Jeremy Wohlwend, Adam Yala, Ludvig Karstens, Justin
Xiang, Angelo K. Takigami, Patrick P. Bourgouin, et al. “Sybil: A
Validated Deep Learning Model to Predict Future Lung Cancer Risk From
a Single Low-Dose Chest Computed Tomography.” Journal of Clinical
Oncology 41, no. 12 (April 20, 2023): 2191–2200.

Leslie R. Lamb et al. Deep learning vs traditional breast cancer risk
assessment models: Are we offering supplemental services to those who
benefit the most?. JCO 42, 1556-1556(2024).
DOI:10.1200/JCO.2024.42.16_suppl.1556

Zhu, Simeng, Marissa Gilbert, Indrin Chetty, and Farzan Siddiqui. “The
2021 Landscape of FDA-Approved Artificial Intelligence/Machine
Learning-Enabled Medical Devices: An Analysis of the Characteristics
and Intended Use.” International Journal of Medical Informatics 165
(September 2022): 104828.

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