Medical Xpress October 22, 2024
Researchers at UT Southwestern Medical Center have developed a machine learning model that can identify patients with diabetic cardiomyopathy, a heart condition characterized by abnormal changes in the heart’s structure and function that predisposes them to an increased risk of heart failure.
The findings, published in the European Journal of Heart Failure, offer a data-driven method to detect a high-risk diabetic cardiomyopathy phenotype, enabling early interventions that could help prevent heart failure in this vulnerable population.
“This research is noteworthy because it uses machine learning to provide a comprehensive characterization of diabetic cardiomyopathy—a condition that has lacked a consensus definition—and identifies a high-risk phenotype that could guide more targeted heart failure prevention strategies in patients with diabetes,” said senior author...
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