Artificial Intelligence and Histopathological Characterization of Microscopy Images With the recent expansions of whole-slide digital scanning, archiving, and high-throughput tissue banks, the field of digital pathology is primed to benefit significantly from deep learning technology. This talk will cover several applications of deep learning for characterizing histologic patterns on high-resolution microscopy images for cancerous and precancerous lesions. Also, recent advances and future directions for developing and evaluating deep learning models for pathology image analysis will be discussed.
Dr. Saeed Hassanpour is an Associate Professor in the Departments of Biomedical Data Science, Computer Science, and Epidemiology at Dartmouth College. His research is focused on the use of artificial intelligence in healthcare. Dr. Hassanpour’s research laboratory has built novel machine learning and deep learning models for medical image analysis and clinical text mining to improve diagnosis, prognosis, and personalized therapies. Before joining Dartmouth, he worked as a Research Engineer at Microsoft. Dr. Hassanpour received his Ph.D. in Electrical Engineering with a minor in Biomedical Informatics from Stanford University and a Master of Math in Computer Science from the University of Waterloo in Canada.