One of the critical bottlenecks in implementing genomics in the critical care setting remains the availability of rapid analytic platforms. In this plenary session, the speaker will describe ultra-rapid whole genome sequencing (urWGS) for diagnosis and management of children in intensive care units. You will learn about the application of machine learning and clinical natural language processing algorithms to perform urWGS as well as the indications, clinical utility of WGS in ICUs, and the impact of urWGS on healthcare utilization in children's hospital systems.
Machine Learning in Genomic Medicine
Stephen F. Kingsmore, MD DSc FRCPath, Rady Children's Institute for Genomic Medicine, San Diego, CA, USA
Objectives:
- Understand the indications and clinical utility of urWGS.
- Understand the role of machine learning algorithms in urWGS.
Recording Date: November 19, 2020
Continuing Education Credit Information
CME/CMLE credit: 1.00 hr
Last day to purchase course and CE claim credit: February 16, 2024
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