Machine Learning–Based Early Warning Systems for Clinical Deterioration: Systematic Scoping Review

Explainable artificial intelligence model to predict acute critical illness from electronic health records

(2020) Simon Meyer Lauritsen et al.   Nature Communications

CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization

(2020) Zijie J. Wang et al.   IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS

The value of vital sign trends in predicting and monitoring clinical deterioration: A systematic review

(2019) Idar Johan Brekke et al.   PLoS One

Predicting tachycardia as a surrogate for instability in the intensive care unit

(2019) Joo Heung Yoon et al.   JOURNAL OF CLINICAL MONITORING AND COMPUTING

Heart rate variability based machine learning models for risk prediction of suspected sepsis patients in the emergency department

(2019) Calvin J. Chiew et al.   MEDICINE

Developing neural network models for early detection of cardiac arrest in emergency department

(2019) Dong-Hyun Jang et al.   AMERICAN JOURNAL OF EMERGENCY MEDICINE

Incidence, Severity, and Detection of Blood Pressure Perturbations after Abdominal Surgery

(2019) Alparslan Turan et al.   ANESTHESIOLOGY

Logistic early warning scores to predict death, cardiac arrest or unplanned intensive care unit re‐admission after cardiac surgery

(2019) Y.‐D. Chiu et al.   ANAESTHESIA

Association between complications and death within 30 days after noncardiac surgery

(2019)   CANADIAN MEDICAL ASSOCIATION JOURNAL

Do no harm: a roadmap for responsible machine learning for health care

(2019) Jenna Wiens et al.   NATURE MEDICINE

Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU

(2018) Qingqing Mao et al.   BMJ Open

An Algorithm Based on Deep Learning for Predicting In‐Hospital Cardiac Arrest

(2018) Joon‐myoung Kwon et al.   Journal of the American Heart Association

PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation

(2018) Andrea C. Tricco et al.   ANNALS OF INTERNAL MEDICINE

Towards an automated multimodal clinical decision support system at the post anesthesia care unit

(2018) Rasmus Munch Olsen et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Clinical Implications and Challenges of Artificial Intelligence and Deep Learning

(2018) William W. Stead   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Validation of deep-learning-based triage and acuity score using a large national dataset

(2018) Joon-myoung Kwon et al.   PLoS One

Artificial Intelligence to Prevent Mobile Heart Failure Patients Decompensation in Real Time: Monitoring-Based Predictive Model

(2018) Nekane Larburu et al.   Mobile Information Systems

Unintended Consequences of Machine Learning in Medicine

(2017) Federico Cabitza et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Early sepsis detection in critical care patients using multiscale blood pressure and heart rate dynamics

(2017) Supreeth P. Shashikumar et al.   JOURNAL OF ELECTROCARDIOLOGY

PEACE-Home: Probabilistic estimation of abnormal clinical events using vital sign correlations for reliable home-based monitoring

(2017) Abdur Rahim Mohammad Forkan et al.   Pervasive and Mobile Computing

Learning temporal rules to forecast instability in continuously monitored patients

(2016) Mathieu Guillame-Bert et al.   JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION

The value of vital sign trends for detecting clinical deterioration on the wards

(2016) Matthew M. Churpek et al.   RESUSCITATION

MIMIC-III, a freely accessible critical care database

(2016) Alistair E.W. Johnson et al.   Scientific Data

Postoperative Hypoxemia Is Common and Persistent

(2015) Zhuo Sun et al.   ANESTHESIA AND ANALGESIA

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): the TRIPOD Statement

(2015) G. S. Collins et al.   BRITISH JOURNAL OF SURGERY

Adaptive online monitoring for ICU patients by combining just-in-time learning and principal component analysis

(2015) Xuejian Li et al.   JOURNAL OF CLINICAL MONITORING AND COMPUTING

Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection

(2014) Nan Liu et al.   BMC Medical Informatics and Decision Making

Big Data In Health Care: Using Analytics To Identify And Manage High-Risk And High-Cost Patients

(2014) David W. Bates et al.   HEALTH AFFAIRS

Predictive Monitoring of Mobile Patients by Combining Clinical Observations With Data From Wearable Sensors

(2014) Lei Clifton et al.   IEEE Journal of Biomedical and Health Informatics

Using Electronic Health Record Data to Develop and Validate a Prediction Model for Adverse Outcomes in the Wards*

(2013) Matthew M. Churpek et al.   CRITICAL CARE MEDICINE

The ability of the National Early Warning Score (NEWS) to discriminate patients at risk of early cardiac arrest, unanticipated intensive care unit admission, and death

(2013) Gary B. Smith et al.   RESUSCITATION

Decision-tree early warning score (DTEWS) validates the design of the National Early Warning Score (NEWS)

(2013) Tessy Badriyah et al.   RESUSCITATION

Abnormal vital signs are strong predictors for intensive care unit admission and in-hospital mortality in adults triaged in the emergency department - a prospective cohort study

(2012) Charlotte Barfod et al.   Scandinavian Journal of Trauma Resuscitation & Emergency Medicine

ViEWS—Towards a national early warning score for detecting adult inpatient deterioration

(2010) David R. Prytherch et al.   RESUSCITATION

Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement

(2009) David Moher et al.   PLOS MEDICINE

A review, and performance evaluation, of single-parameter “track and trigger” systems

(2008) Gary B. Smith et al.   RESUSCITATION