AI and deep learning in cardiovascular imaging: risk stratification to precision phenotyping

AI and deep learning are moving cardiovascular imaging beyond visual interpretation toward integrated risk stratification and precision phenotyping, but real-world generalizability still needs further validation before guiding individual patient management.

• AI applications for automated image processing and analysis across modalities (CXR, CT, CTA, cardiac MR, echo, nuclear) are relatively mature and validated for improving efficiency.
• AI methods that infer cardiovascular risk or disease phenotype beyond conventional human-defined metrics remain early-stage, requiring further standardization, validation, and clinical evaluation.
• Intended audience: radiologists, cardiologists, and trainees involved in cardiovascular imaging interpretation and management.

Automated summary

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