Exploration of Cardiology

From: How algorithms are transforming the diagnosis of ischemic heart disease—state of the art

Table 5. Clinical and economic outcomes.

Aspect	Value	Details	References
Diagnostic accuracy	Sensitivity 85–95%; Specificity 80–92%	Meta-analyses of ML for CAD detection across imaging modalities; AI performance comparable to expert readers	[9, 47]
Cost savings	20–40% (projected)	Early economic analyses of health systems implementing AI diagnostics; the magnitude depends on integration, training, and adoption	[36]
Time savings	Seconds vs. minutes per imaging study	Automated preliminary reads shorten per-study assessment; potential gains in triage and turnaround times	[35, 55]
Expert agreement	≥ 85% (task-specific)	HD-IVUS agreement with experts: lumen 85% and stent area 97%; AI-assisted stress ECHO non-inferior, with improved consistency for less-experienced readers	[22, 40]

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AI: artificial intelligence; CAD: coronary artery disease; HD-IVUS: high-definition intravascular ultrasound; ML: machine learning; ECHO: echocardiography.

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MT: Conceptualization, Writing—original draft, Writing—review & editing. The author read and approved the submitted version.

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