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Artificial intelligence in ischemic heart disease diagnosis across eras and modalities. The figure illustrates how AI enhances clinical decision-making through improved analysis of <t>ECG</t> signals, cardiac imaging, biomarkers, and risk assessment, marking a shift from traditional methods to integrated predictive analytics. Five images are from Vecteezy.Com (Vectors by Vecteezy, free license), and one image is from Wikimedia Commons (by BruceBlaus, CC BY-SA 4.0).
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Artificial intelligence in ischemic heart disease diagnosis across eras and modalities. The figure illustrates how AI enhances clinical decision-making through improved analysis of ECG signals, cardiac imaging, biomarkers, and risk assessment, marking a shift from traditional methods to integrated predictive analytics. Five images are from Vecteezy.Com (Vectors by Vecteezy, free license), and one image is from Wikimedia Commons (by BruceBlaus, CC BY-SA 4.0).

Journal: Annals of Medicine and Surgery

Article Title: The role of artificial intelligence in early detection and risk prediction of ischemic heart disease

doi: 10.1097/MS9.0000000000004812

Figure Lengend Snippet: Artificial intelligence in ischemic heart disease diagnosis across eras and modalities. The figure illustrates how AI enhances clinical decision-making through improved analysis of ECG signals, cardiac imaging, biomarkers, and risk assessment, marking a shift from traditional methods to integrated predictive analytics. Five images are from Vecteezy.Com (Vectors by Vecteezy, free license), and one image is from Wikimedia Commons (by BruceBlaus, CC BY-SA 4.0).

Article Snippet: Wu et al , 2023 [ ] , 9340 ED ECGs , 12-lead ECG , Compare CIE vs physician STEMI reads , Philips DXL (rule-based) , Retrospective , Physicians: AUC: 0.94; DXL: 0.86 , Human reads more accurate , Single-center; non-ML model.

Techniques: Biomarker Discovery, Imaging