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. Author manuscript; available in PMC: 2024 Jan 1.
Published in final edited form as: Ann Emerg Med. 2022 Oct 15;81(1):57–69. doi: 10.1016/j.annemergmed.2022.08.005

Figure 2: Classification performance of NSTE-ACS using AI-augmented ECG analysis.

Figure 2:

This figure shows random forest classification performance using features from prehospital ECG (AI-PH-ECG) or the emergency department (AI-ED-ECG) as compared to clinical practice based on ED evaluation (CP-ED-ECG) on both training subset (left) and testing subset (right). The tables show the diagnostic accuracy measures and the net reclassification performance (NRI) index as compared to CP-ED-ECG as a reference standard (Ref).