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Watch a comprehensive lecture by Harvard Medical School Assistant Professor Dr. Faisal Mahmood exploring the intersection of artificial intelligence and digital pathology, covering data-efficient methods for whole slide classification in cancer diagnosis, identifying origins of unknown primary cancers, developing interpretable multimodal deep learning for prognostic markers, implementing models in resource-limited settings, and addressing bias in computational pathology algorithms. Learn from Dr. Mahmood's expertise as the head of the Division of Computational Pathology at Brigham and Women's Hospital, where his research focuses on pathology image analysis, morphological feature discovery, and multimodal analysis techniques that are advancing objective diagnosis, prognosis, and therapeutic response prediction in medical practice.
