Shah Lab
Principal Investigator: Svati H. Shah
Institution: Duke University (Durham, NC)
Primary Subfield: Computational Biology
Recruitment Status: Inquire for rotation/fellowship opportunities
Research Focus
Monogenic disorders individually are rare but in aggregate are common, with estimates of up to 1 in 40 individuals afflicted. In monogenic cardiovascular (CV) disease, early identification of at-risk individuals has proven utility for prevention. Unfortunately, there is substantial clinical variability not only in identification of monogenic CV diseases but also in therapeutic interventions for these patients, in part because of their underdiagnosis. As such, there is a need for development of more targeted approaches for identification of monogenic CV disorders, but that go beyond traditional diagnostic models that result in underdiagnosis. There is an opportunity and need to integrate cutting-edge, high-throughput phenotyping approaches with genetics to identify patients at high risk, or already showing evidence of monogenic CV disorders, and determine if this approach can improve the care of these patients. The overall objective for this proposal is to develop, validate and determine clinical utility of a precision genetic testing approach guided by machine learning (ML)-based models. We hypothesize that ML electronic health record (EHR), genetic and imaging algorithms coupled w…
Active NIH Awards
- 5R01HL168940-03: Machine Learning Guided Precision Genetic Testing for Identification of Monogenic Cardiovascular Disorders (2026)
- 5R01HL168940-02: Machine Learning Guided Precision Genetic Testing for Identification of Monogenic Cardiovascular Disorders (2025)
- 1R01HL168940-01A1: Machine Learning Guided Precision Genetic Testing for Identification of Monogenic Cardiovascular Disorders (2024)
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