Machine Learning Computer Vision Point of Care Decision Support of Echocardiographic Identification of Hypertrophic Cardiomyopathy
A machine learning CNN with model prediction visualization optimized for clinical implementation identifies all HCM morphologic subtypes. Further work is necessary to validate model performance in external data and real-world use.
Authors
- Karen Chiswell (ORCID: https://orcid.org/0000-0002-0279-9093)
- Anru R. Zhang (ORCID: https://orcid.org/0000-0002-8721-5252)
- Ricardo Henao (ORCID: https://orcid.org/0000-0003-4980-845X)
- Pamela S. Douglas (ORCID: https://orcid.org/0000-0001-9876-4049)
- Fawaz Alenezi (ORCID: https://orcid.org/0000-0001-8171-2250)
- Anna Giczewska (ORCID: https://orcid.org/0000-0003-0533-2453)
- Sreekanth Vemulapalli (ORCID: https://orcid.org/0000-0003-1599-2957)
- Hyeon Ki Jeong (ORCID: https://orcid.org/0000-0001-6680-2012)
- Svati Shah
Institutions
- Duke University (US)
- Clinical Research Institute (US)
- Duke Medical Center (US)
- King Abdullah University of Science and Technology (SA)
Publication Details
- Journal
- JACC Advances
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1016/j.jacadv.2025.101746
- Citations
- 4
- Primary Topic
- Cardiomyopathy and Myosin Studies
- Type
- article
- Field-Weighted Citation Impact
- 5.55
Funders
- Cytokinetics