Accuracy of Machine Learning Models to Predict In-hospital Cardiac Arrest

Detecting Patient Deterioration Using Artificial Intelligence in a Rapid Response System

(2020) Kyung-Jae Cho et al.   CRITICAL CARE MEDICINE

PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies

(2019) Robert F. Wolff et al.   ANNALS OF INTERNAL MEDICINE

Applications of artificial neural networks in health care organizational decision-making: A scoping review

(2019) Nida Shahid et al.   PLoS One

In-Hospital Cardiac Arrest

(2019) Lars W. Andersen et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Predicting Cardiac Arrest and Respiratory Failure Using Feasible Artificial Intelligence with Simple Trajectories of Patient Data

(2019) Jeongmin Kim et al.   Journal of Clinical Medicine

Comparison of the Between the Flags calling criteria to the MEWS, NEWS and the electronic Cardiac Arrest Risk Triage (eCART) score for the identification of deteriorating ward patients

(2018) Malcolm Green et al.   RESUSCITATION

Toward analyzing and synthesizing previous research in early prediction of cardiac arrest using machine learning based on a multi-layered integrative framework

(2018) Samaneh Layeghian Javan et al.   JOURNAL OF BIOMEDICAL INFORMATICS

Prediction Is Difficult, Especially About Future Unexpected Deterioration*

(2016) Andrew J. E. Seely   CRITICAL CARE MEDICINE

Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the Wards

(2016) Matthew M. Churpek et al.   CRITICAL CARE MEDICINE

Modified Early Warning Score Changes Prior to Cardiac Arrest in General Wards

(2015) Won Young Kim et al.   PLoS One

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

Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies: The CHARMS Checklist

(2014) Karel G. M. Moons et al.   PLOS MEDICINE

Measuring the modified early warning score and the Rothman Index: Advantages of utilizing the electronic medical record in an early warning system

(2013) G. Duncan Finlay et al.   Journal of Hospital Medicine

Receiver Operating Characteristic Curve in Diagnostic Test Assessment

(2010) Jayawant N. Mandrekar   Journal of Thoracic Oncology

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

(2009) David Moher et al.   PLOS MEDICINE