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- W4308149553 abstract "The idea that we can detect subacute potentially catastrophic illness earlier by using statistical models trained on clinical data is now well-established. We review evidence that supports the role of continuous cardiorespiratory monitoring in these predictive analytics monitoring tools. In particular, we review how continuous ECG monitoring reflects the patient and not the clinician, is less likely to be biased, is unaffected by changes in practice patterns, captures signatures of illnesses that are interpretable by clinicians, and is an underappreciated and underutilized source of detailed information for new mathematical methods to reveal." @default.
- W4308149553 created "2022-11-08" @default.
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- W4308149553 date "2023-01-01" @default.
- W4308149553 modified "2023-10-18" @default.
- W4308149553 title "Continuous ECG monitoring should be the heart of bedside AI-based predictive analytics monitoring for early detection of clinical deterioration" @default.
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- W4308149553 doi "https://doi.org/10.1016/j.jelectrocard.2022.10.011" @default.
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- W4308149553 hasPublicationYear "2023" @default.
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