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. Author manuscript; available in PMC: 2024 Apr 24.
Published in final edited form as: Circulation. 2024 Feb 28;149(14):e1028–e1050. doi: 10.1161/CIR.0000000000001201

Table 5.

Genetics

Best practices Description
AI/ML algorithms predict common cardiovascular disease (coronary artery disease, diabetes, hypertension, arrhythmia) using personal genomics Effective preventive medicine and clinical surveillance may be used to decrease cardiovascular disease morbidity and mortality for large, at-risk populations.
AI/ML algorithm-based identification of monogenic causes of cardiovascular disease, for targeted drug development Discovery of genes that cause cardiovascular disease identify potential targets for highly efficacious novel drug therapies (eg, statin drugs).
AI/ML algorithm-based classification improvement for predicting rare genetic variants as benign or pathogenic Targeted genetic testing in clinical genetics is fraught with the frequent observation of genetic variants of uncertain relevance.
Gaps and challenges Description
Implementation of universal standards to clinically translate genomic AI/ML algorithms AI/ML-based models must be validated and robust in prediction for routine use in clinical genetics.

AI indicates artificial intelligence; and ML, machine learning.