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MIA Talks

Primer: Advancements and challenges for deep learning in medical imaging

October 6, 2021
Dept. of Biomedical Informatics, Harvard Medical School

There have been rapid advances at the intersection of AI and medicine over the last few years, especially for the interpretation of medical images. In this talk, I will describe three key directions that present challenges and opportunities for the development of deep learning technologies for medical image interpretation. First, I will discuss the development of transfer learning and self-supervised learning algorithms designed to work in low labeled medical data settings. Second, I will discuss the design and curation of large, high-quality datasets and their roles in advancing algorithmic developments. Third, I will discuss the real-world impact of AI technologies on clinicians’ decision making and subtleties for the promise of expert-AI collaboration. Altogether I will summarize key recent contributions and insights in each of these directions with key applications across medical specialties.