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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Please join the School of CSE on Feb. 17 at 11 a.m. for a webinar presentation by King’s College London Professor Steve Niederer His talk is titled Computational Cardiology: Integrating Physics, Physiology and Clinical Data
To join the meeting:
BlueJeans Link: https://bluejeans.com/559999271/8550 Passcode 8550
Abstract: Precision medicine is emerging as the future of cardiology. Clinical decisions for cardiology patients increasingly rely on advanced imaging technology, genetic profiling, pharmaceuticals, and medical devices. However, current guidelines are still informed by population averages, decisions are made on the current state of the patient, and clinical data are often not interpreted in the context of known physiology and physics. Computational cardiology aims to provide a common quantitative framework, informed by physics and physiology, to integrate and interpret clinical data to inform patient decisions. Representing patient data in predictive frameworks allows patients to be treated on their expected outcome from therapy, not just their current state. In addition, creating patient-specific models allows therapies to be tailored to the individual. Further, as increasing numbers of patient-specific models are created, this provides a framework for rapidly testing pre-clinical hypotheses in patients, evaluating novel biomarkers, synthesizing training data for machine learning algorithms, and testing innovative devices through in-silico trials. Our work focuses on an integrated clinic-to-model and back again workflow. In this presentation, I will describe our work on pre-clinical, atrial fibrillation, and heart failure applications, focusing on the technical challenges in creating and deploying applied cardiac models at scale.
