November 21 Nov 21
12:00 PM - 01:00 PM
12:00 PM - 01:00 PM
Stanford University School of Medicine291 Campus Dr
Stanford, CA 94305
Medical Physics Seminar - Saad Nadeem
Building a comprehensive multimodal/multiscale patient snapshot for improved clinical outcomes
Webinar URL: https://stanford.zoom.us/webinar/register/WN_j1zCOA3wTUaOW1k9ue6zHQ
Dial: US: +1 650 724 9799 or +1 833 302 1536 (Toll Free)
Webinar ID: 981 4830 1798
Sponsored by the Radiation Oncology, Division of Medical Physics
Dr. Saad Nadeem, Assistant Professor in the Departments of Medical
Physics and Pathology at Memorial Sloan Kettering Cancer Center.
Dr. Saad Nadeem is an Assistant Professor in the Departments of Medical Physics and Pathology at Memorial Sloan Kettering Cancer Center. His lab develops advanced mathematical and machine learning techniques for analyzing patient data at multiple scales (macro: radiology/surgery, meso: pathology, and micro: molecular - genomics/proteomics/transcriptomics/metabolomics) to improve patient outcomes. The lab is specifically focused on building user-friendly tools that seamlessly fit into the clinical workflows and facilitate accurate and timely diagnosis/prognosis/decision-making while aiding in novel biomarker discovery.
Gleaning rigorous clinical insights from radiology scans, surgical videos, and pathology slides provides a comprehensive patient snapshot for more informed decision-making. In this talk, I will present our broader effort to weave information from these complementary modalities/scales to improve patient outcomes. Specifically, for radiology scans, I will introduce our work on (1) creating clinically-interpretable radiomics for screening and treatment response prediction, (2) artifacts: friends or foe?, (3) physically-realistic breathing motion induction in static scans, and (4) clinically-deliverable radiation dose prediction using AI and large-scale optimization. For surgery, I will briefly talk about our pioneering work in analyzing minimally invasive surgical videos. I will conclude with our work in pathology which aims to bridge hematoxylin-and-eosin (H&E), immunohistochemistry (IHC), and next-generation multiplex image analysis for improved biomarker quantification.