Dreyer, Criminisi Discuss Machine Learning in RSNA/AAPM Symposium Today
Tuesday, Nov. 28, 2017
Keith J. Dreyer, DO, PhD, and Antonio Criminisi, PhD, will help radiologists and medical physicists further understand the current and potential impacts of machine learning (ML) and artificial intelligence (AI) on radiology in a symposium presented today in conjunction with the American Association of Physicists in Medicine (AAPM).
Dr. Dreyer will discuss how radiology can utilize ML and AI to improve the quality and relevance of imaging as well as benefit patients, while Dr. Criminisi will speak on the potential of assistive AI for cancer treatment. The session will be moderated by Paul E. Kinahan, PhD.
Dr. Dreyer is vice chair of radiology and director of the Center for Clinical Data Science at Massachusetts General Hospital in Boston, and associate professor of radiology at Harvard Medical School. He is a renowned informatics expert and has conducted research in clinical data science, cognitive computing, clinical decision support, clinical language understudying and digital imaging standards. He is particularly interested in the implications of technology for the quality of healthcare and payment reform initiatives.
He has served on the RSNA RadLex Steering Committee, the Imaging Informatics Coalition and as an annual meeting session and plenary moderator. He currently serves on the board of chancellors of the American College of Radiology (ACR) and is the chair of the commission on informatics. Dr. Dreyer has also served on numerous committees of the Society of Imaging Informatics in Medicine (SIIM).
Dr. Criminisi is a principal researcher at Microsoft in Cambridge, United Kingdom. His areas of research include AI, ML, computer vision and medical image analysis. Dr. Criminisi is leading Microsoft's InnerEye project that uses state of the art AI to build innovative image analysis tools to help doctors treat diseases such as cancer in a more targeted and effective way. He is the author of numerous scientific papers and books and in 2015, he received the David Marr Best Paper Prize from the International Conference on Computer Vision for his co-authored paper on deep neural decision forests.