Robust artificial intelligence tools to predict future cancer

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 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. But to integrate image-based risk models into clinical care and make them widely available, the researchers say the models needed both algorithmic improvements and large-scale validation across several hospitals to prove their robustness.