While no one doubts the potential of AI as a tool for radiologists, there are still too few training curricula in AI and Machine Learning for resident radiologists.
To help rectify that problem, three senior radiology residents at Brigham and Women's Hospital (BWH) in Boston recently helped devise a data science pathway to provide a well-rounded introductory experience in AI-ML for fourth-year residents. The pathway combines formal instruction with practical problem-solving in collaboration with data scientists.
As explained in a report on the project at Radiology: Artificial Intelligence, “Data science has the potential to reinvigorate our specialty, but radiologists must be ready and able to adapt to changes in practice in the coming years. Radiologists-in-training should embrace data science in preparation for guiding machine learning model development and application translation into the clinical arena.”
To that end, the pathway aims to provide residents with an immersion into AI and machine learning through a flexible schedule of educational, experimental, and research activities at Massachusetts General Hospital (MGH) and BWH Center for Clinical Data Science (CCDS).
"Across the nation there are a number of radiology residency programs that are trying to figure out how to integrate AI into their training," said the paper's co-lead author Walter F. Wiggins, M.D., Ph.D. "We thought that perhaps our experience would help other programs figure out ways to integrate this type of training into either their elective pathways or their more general residency curriculum.”
Through the pathway, Dr. Wiggins and resident colleagues were exposed to all aspects of AI and machine learning application development, such as data curation, model design, quality control, and clinical testing. Residents contributed to model and tool development at different stages, and their work during the pilot led to 12 accepted abstracts for presentation at national meetings.
Feedback from the pilot project led to the establishment of a formal AI and machine learning curriculum for future residents.
The pathway provided numerous opportunities for the residents to work directly with data scientists to better understand how they approach image analysis problems with ML tools. This partnership, in turn, helped the data scientists better understand how radiologists approach a radiology problem in a clinical setting.
"Radiologists have always had to manage, analyze and process data in order to be able to do their work," Dr. Wiggins said. "We already have the underlying skill sets and infrastructure that we can tap into to allow residents with an interest in AI and ML to really develop and become leaders in applying these skills clinically."
The senior year of radiology residency is an ideal time for immersive involvement in a curriculum covering essential skills in data science, AI and ML, noted the report.