Ask us anything about the use of machine learning in radiology – how it’s in use today, what is coming in the future for how these algorithms could impact research and clinical care!
We are Dr. Eric Stern, professor of radiology at University of Washington, Dr. Mark Michalski, radiologist and Director of the Center for Clinical Data Science at Mass General and Brigham and Women's Hospitals, and Dr. Anna Fernandez, biomedical engineer with focus on medical imaging and precision-medicine related informatics and part of the Data Science Bowl team at Booz Allen Hamilton.
Dr. Stern specializes in thoracic imaging including lung cancer screening and Dr. Michalski specializes in data science for medical imaging. On behalf of our organizations and as members of the American College of Radiology, we support the effort to drive data scientists to develop new and advanced machine learning algorithms for lung cancer via the Data Science Bowl presented by Booz Allen Hamilton and Kaggle. We are part of a broader team that have collaborated together for this year’s Data Science Bowl focused on lung cancer. In addition to our organizations, the NCI provided the data and focus with the support of the National Lung Screening Trial; The Cancer Imaging Archive; Diagnostic Image Analysis Group, Radboud University; Lahey Hospital and Medical Center; and Copenhagen University Hospital. By putting data science to work in the lung-cancer field, we continue to open up the use of advanced machine learning techniques across radiology. Moving away from just nodule detection – what other features can be extracted from the images that can help improve our ability to assess lung cancer risk or staging?
How will the use of machine learning be put into practice for improved clinical care? Share your perspectives and ask us anything!
We will be back at 12 pm ET to answer your questions, ask us anything!
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