Exploration of Cardiology

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

Table 7. Applications by diagnostic stage.

Stage	AI tools	Main benefits	References
Screening	AI-ECG	Early detection of latent disease and population-level risk prediction/triage	[6, 17]
Anatomical diagnosis	AI-CCTA; AI-CMR	Accurate plaque quantification and characterization (CCTA); quantitative myocardial tissue characterization, including LGE/T1 mapping (CMR)	[7, 10, 11, 21]
Functional assessment	AI-FFR (FFR-CT); AI-perfusion (stress imaging: echocardiography/nuclear)	Non-invasive hemodynamic evaluation; lesion-specific ischemia assessment; potential improvement of reader performance in stress imaging	[9, 32, 33, 36, 40]
Intervention planning	AI-IVUS; AI-OCT	Procedure optimization (e.g., stent sizing and landing zone selection), outcome prediction, and intraprocedural decision support	[13, 22, 39]
Monitoring	Integrated CDSS (with imaging and ECG data)	Personalized risk stratification, longitudinal follow-up, and event prediction with integration of multimodal data into clinical workflows	[16, 18, 52]

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AI: artificial intelligence; CCTA: coronary computed tomography angiography; CDSS: clinical decision support systems; CMR: cardiovascular magnetic resonance; CT: computed tomography; FFR: fractional flow reserve; FFR-CT: FFR derived from CT; ECG: electrocardiogram; IVUS: intravascular ultrasound; LGE: late gadolinium enhancement; OCT: optical coherence tomography.

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

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