What is AI for Digital Pathology?
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Artificial Intelligence (AI) uses computer systems to emulate human intelligence processes such as visual perception, decision-making, and communication. Advances in AI technology and associated technology such as cloud storage and faster computer processors have paved the way for applying AI in digital image processing. Concurrently, the adoption of Digital Pathology (DP) has ushered in an era wherein AI can be used to process Whole Slide Images (WSI) and glean clinically relevant information from WSIs.
This talk is designed to explain current digital pathology use-cases such as tumor detection, grading, and subtyping. Further, the talk will demystify the underlying AI principles in advanced WSI analysis such as mutation prediction, survival prediction, multiplexing, spatial transcriptomics, and virtual staining. Finally, the talk will highlight current initiatives to integrate data from microscopic and macroscopic levels to strengthen pathology decision-making.
CEUs: This histology course is worth 1 continuing education credit. Course is available for 365 days from date of purchase.
Anindita Sarkar, PhD
Sr. Manager – AI Program Management, Artificial Intelligence & Machine Learning
Leica Biosystems, a Danaher company
Anindita Sarkar is a Scientist-turned- entrepreneur. She has extensive experience in initiating and managing early stage product development – small molecule drug and AI-Biology software. She has a Wide-range of experience in startup operational roles – accounting, finance, project management, business development, and external contract organizations. Dr. Sarkar is experienced in diverse scientific areas such as musculoskeletal disorders, urinary disorders, GI immune disorder, breast cancer, and synthetic biology. She is recognized for initiating bold projects, resuscitating programs, cultivating business relationships, and thriving in diverse and collaborative environments.