Event date:
Dec 15 2022 3:00 pm

Building a comprehensive multimodal/multiscale patient snapshot for improved clinical outcomes

Speaker(s)
Dr. Saad Nadeem, Memorial Sloan Kettering Cancer Center (MSKCC)
Venue
CS Smart Lab, (Ground Floor) SSE Building
Abstract
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 radiation treatment planning using AI and large-scale optimization. For surgery, I will talk about our work on analyzing minimally invasive surgical videos. I will conclude with our work in pathology that bridges digitized clinical and next-generation stained image analysis for improved biomarker quantification. All this work is driven by highest-quality opensource implementations.

Dr. Saad Nadeem is an Assistant Professor in the Departments of Medical Physics and Pathology at Memorial Sloan Kettering Cancer Center (MSKCC). He completed his PhD in Computer Science from Stony Brook University in 2017 and his postdoc from MSKCC in 2019 before transitioning to an Assistant Professor position. His lab develops advanced mathematical and machine learning techniques for analyzing patient data at multiple scales (macro: radiology/radiation oncology/surgery/endoscopy, 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.