Does a cardiovascular deep learning model accurately identify subtle changes in LV wall geometric measurements and causes of hypertrophy compared to human experts?
A fully automated deep learning workflow can accurately and reproducibly phenotype left ventricular hypertrophy, potentially improving precision diagnosis over human experts.
In this cohort study, the deep learning model accurately identified subtle changes in LV wall geometric measurements and the causes of hypertrophy. Unlike with human experts, the deep learning workflow is fully automated, allowing for reproducible, precise measurements, and may provide a foundation for precision diagnosis of cardiac hypertrophy.
Duffy et al. (Wed,) studied this question.
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