1. RSNA-MICCAI Panel Discussion: Machine Learning for Radiology from Challenges to Clinical Applications.
- Author
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Mongan, John, Kalpathy-Cramer, Jayashree, Flanders, Adam, and George Linguraru, Marius
- Subjects
Artificial Neural Network Algorithms ,Back-Propagation ,Machine Learning Algorithms - Abstract
On October 5, 2020, the Medical Image Computing and Computer Assisted Intervention Society (MICCAI) 2020 conference hosted a virtual panel discussion with members of the Machine Learning Steering Subcommittee of the Radiological Society of North America. The MICCAI Society brings together scientists, engineers, physicians, educators, and students from around the world. Both societies share a vision to develop radiologic and medical imaging techniques through advanced quantitative imaging biomarkers and artificial intelligence. The panel elaborated on how collaborations between radiologists and machine learning scientists facilitate the creation and clinical success of imaging technology for radiology. This report presents structured highlights of the moderated dialogue at the panel. Keywords: Back-Propagation, Artificial Neural Network Algorithms, Machine Learning Algorithms © RSNA, 2021.
- Published
- 2021