ReviewJournal of electrocardiology
Continuous ECG monitoring should be the heart of bedside AI-based predictive analytics monitoring for early detection of clinical deterioration.
Review in Journal of electrocardiology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- Bridging the Theory-Practice Divide in ECG Education: A Multistakeholder Qualitative Inquiry.Nursing open · 2026Article
- Cardiovascular and Autonomic Phenotypes Reveal Distinct Mechanisms of Sepsis Decompensation via Deep Learning.Research square · 2026Article
- Time-series ECG Imputation Using a Pattern-Based Masking Framework.medRxiv : the preprint server for health sciences · 2026Article
- Systematic Review of Artificial Intelligence and Electrocardiography for Cardiovascular Disease Diagnosis.Bioengineering (Basel, Switzerland) · 2025Review
- A Review of Racial Differences and Disparities in ECG.International journal of environmental research and public health · 2025Review
- Assessment of Physiological Signals from Photoplethysmography Sensors Compared to an Electrocardiogram Sensor: A Validation Study in Daily Life.Sensors (Basel, Switzerland) · 2024Article
- Searching for atrial fibrillation post stroke: is it time for digital devices?Frontiers in cardiovascular medicine · 2023Review
- CNN and SVM-Based Models for the Detection of Heart Failure Using Electrocardiogram Signals.Sensors (Basel, Switzerland) · 2022Article
- A narrative review of AI monitoring in postoperative pain management and functional rehabilitation for spinal cord injury.Frontiers in neurologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 4 institutions in 1 country.
Funding
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.