Researchers introduced CARDEA, an AI system for end-to-end coronary angiography (CAG) interpretation that grounds its reasoning in spatial evidence to make decisions auditable, according to the paper's description. The work targets observer variability in CAG, the gold standard for diagnosing coronary artery disease, where existing AI systems improve consistency but lack auditable decision processes and comprehensive open-ended assessment.
Invasive coronary angiography (CAG) is the gold standard for diagnosing coronary artery disease, but interpretation varies substantially among observers. Existing AI systems can improve consistency but lack auditable decision processes and are limited in comprehensive open-ended assessment, undermin
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