－ AI in Medicine: Bridging Innovation & Practice －
CPHAI Symposium
HANOVER INN, GRAND BALLROOM
WEDNESDAY, APRIL 3RD
Overview
Join us for the Inaugural Dartmouth Symposium on Precision Health & AI on April 3rd, at the Hanover Inn Grand Ballroom. This event showcases Dartmouth's forefront in AI and healthcare, featuring keynotes by Dr. Curtis Langlotz and Dr. Faisal Mahmood, and opening remarks by President Sian Leah Beilock. Dartmouth's AI experts and clinicians will share insights into transforming healthcare through AI, emphasizing collaborative research and innovation. Don't miss this opportunity to engage with pioneers in AI-driven healthcare solutions.
Registration
Register now for the CPHAI Symposium to engage with leading experts in AI and healthcare. With limited spaces, this event offers unique learning and networking opportunities. Contribute to the future of precision health by simply filling out the form below.
Venue
Hanover Inn DartmouthTwo East Wheelock
Hanover, New Hampshire, 03755Join us on April 3rd at the Hanover Inn, Grand Ballroom.
Schedule
WEDNESDAY, APRIL 3RD
8:00 - 9:00 AMRegistration and Breakfast9:00 - 9:15 AMWelcome by Dr. Saeed Hassanpour9:15 - 9:30 AMOpening Remarks by President Sian Leah BeilockMorning Keynote by Dr. Curtis Langlotz (Stanford University)9:30 - 10:30 AM10:30 - 11:00 AMCoffee BreakClinician Panel with Drs. Jessica Sin, Jennifer Hong, Louis Vaickus Moderated by Dr. Timothy Burdick11:00 - 12:00 PM12:00 - 1:30 PMLunchAI Alliance Discussion by Dr. Soroush Vosoughi1:30 - 1:45 PMAccelerating Innovation in Healthcare at Dartmouth by Dr. Barry Schweitzer1:45 - 2:00 PMAfternoon Keynote by Dr. Faisal Mahmood (Harvard University)2:00 - 3:00 PM3:00 - 3:45 PMCoffee BreakAI in Education by Dr. Thomas Thesen3:45 - 4:15 PMAI & Genome Informatics by Dr. Parth Shah4:15 - 4:45 PM4:45 - 5:00 PMClosing Remarks by Dr. Saeed Hassanpour5:00 - 6:00 PMReceptionKeynote Presentations
Curtis P. Langlotz, MD, PhD
Stanford University
Dr. Langlotz is Professor of Radiology, Medicine, and Biomedical Data Science, Director of the Center for Artificial Intelligence in Medicine and Imaging (AIMI Center), and Associate Director of the Institute for Human-Centered Artificial Intelligence (HAI) at Stanford University. The AIMI Center comprises over 150 faculty from across Stanford who conduct interdisciplinary machine learning research that optimizes how clinical data are used to promote health. Dr. Langlotz’s laboratory investigates the use of machine learning technologies to help physicians detect disease and eliminate diagnostic errors. He has led many national and international efforts to improve medical imaging, including the RadLex terminology standard and the Medical Imaging and Data Resource Center (MIDRC), an NIH-funded U.S. national imaging research repository.
As Associate Chair for Information Systems and a Medical Informatics Director for Stanford Health Care, he is responsible for the computer technology that supports the Stanford Radiology practice, including 20 million imaging studies that occupy 1.6 petabytes of storage. He currently serves as President of the Radiological Society of North America (RSNA). He has founded three healthcare IT companies, including Montage Healthcare Solutions, which was acquired by Nuance Communications in 2016.
The Future of AI in Medical Imaging
Artificial intelligence (AI) is powerful new tool for building machine learning systems that support the work of clinical imaging professionals. These promising techniques create image analysis systems that perform some image interpretation tasks at the level of clinical experts. Deep learning methods are now being developed for image reconstruction, imaging quality assurance, imaging triage, computer-aided detection, computer-aided classification, and other new imaging insights. The resulting systems have the potential to provide real-time assistance to imaging professionals, thereby reducing diagnostic errors, improving patient outcomes, and reducing costs. We will review the origins of AI and its applications to medical imaging, define key terms, and show examples of real-world systems that suggest how AI may change the practice of medicine. We will also review key shortcomings and challenges that may limit the application of AI to clinical imaging.
Faisal Mahmood, PhD
Harvard University
Dr. Mahmood is an Associate Professor of Pathology at Harvard Medical School and the Division of Computational Pathology at the Brigham and Women's Hospital. He received his Ph.D. in Biomedical Imaging from the Okinawa Institute of Science and Technology, Japan, and was a postdoctoral fellow at the Department of Biomedical Engineering at Johns Hopkins University. Dr. Mahmood directs the pathology image analysis research laboratory, and his research interests include image analysis, morphological feature, and biomarker discovery using data fusion and multimodal analysis. Dr. Mahmood is a full member of the Dana-Farber Cancer Institute / Harvard Cancer Center ; an Associate Member of the Broad Institute of Harvard and MIT, and a member of the Harvard Bioinformatics and Integrative Genomics (BIG) faculty.
