The deep learning model, known as Sybil, predicts future lung cancer risk based on a single low-dose chest CT and can identify individuals who would benefit from regular monitoring.
WEDNESDAY, Jan. 18, 2023 (HealthDay News) A deep learning model can accurately predict future lung cancer risk from a single low-dose computed tomography (LDCT) scan, according to a study published online Jan. 12 in the Journal of Clinical Oncology. Peter G. Mikhael, from the Massachusetts Institute of Technology in Cambridge, and colleagues developed a
Scientists demonstrate that artificial intelligence risk models for breast cancer, paired with AI-designed screening policies, can offer significant and equitable improvements to cancer screening.
Massachusetts Institute of Technology
To catch cancer earlier, we need to predict who is going to get it in the future. The complex nature of forecasting risk has been bolstered by artificial intelligence (AI) tools, but the adoption of AI in medicine has been limited by poor performance on new patient populations and neglect to racial minorities.
Two years ago, a team of scientists from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Jameel Clinic (J-Clinic) demonstrated a deep learning system to predict cancer risk using just a patient’s mammogram. The model showed significant promise and even improved inclusivity: It was equally accurate for both white and Black women, which is especially important given that Black women are 43 percent more likely to die from breast cancer.