Advancing Personalized Cancer Diagnosis, Prognosis and Therapy with AI: Unravelling Tumor Morphology, Microenvironments, and Sharing Knowledge

This seminar will address recent advances in digital/computational histopathology which harnesses the power of artificial intelligence (AI) aiming to expedite and enhance cancer diagnosis, prognosis, and clinical decision-making to the benefit of patients. Additionally, it explores the transformative potential of digital/computational histopathology techniques as effective educational tools for students at every level. Lastly, the seminar outlines a path to translate high-content histopathology data into better mechanistic understanding of cancer microenvironments, with a perspective towards developing digital Virtual Cancer Tissue (VTC) models, and paving the way for personalized Digital Twins of Cancer. *Contents* 00:00 - Introduction 04:54 - Advancing Personalized Cancer Diagnosis, Prognosis and Therapy with AI: Unravelling Tumor Morphology, Microenvironments, and Sharing Knowledge 37:30 - Questions and Discussions Moderator: James Sluka, PhD, Indiana University, Bloomington If you found this video useful, please check out our other videos on computational modeling, infection and immunology: https://youtube.com/playlist?list=PLiEtieOeWbMKh9VcQoinSwODcSZKMTGat Please consider joining our IMAG/MSM WG on Multiscale Modeling and Viral Pandemics: https://www.imagwiki.nibib.nih.gov/content/msm-viral-pandemics-meetings Please also consider joining the Global Alliance for Immune Prediction and Intervention: http://glimprint.org/