Machine Learning Versus Usual Care for Diagnostic and Prognostic Prediction in the Emergency Department: A Systematic Review

Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy

(2020) Lucas M. Fleuren et al.   INTENSIVE CARE MEDICINE

Development and Evaluation of a Machine Learning Model for the Early Identification of Patients at Risk for Sepsis

(2019) Ryan J. Delahanty et al.   ANNALS OF EMERGENCY MEDICINE

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

(2019) Karel G.M. Moons et al.   ANNALS OF INTERNAL 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

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

Machine Learning to Predict Outcomes in Patients with Acute Gastrointestinal Bleeding: A Systematic Review

(2019) Dennis Shung et al.   DIGESTIVE DISEASES AND SCIENCES

Machine Learning in Medicine

(2019) Alvin Rajkomar et al.   NEW ENGLAND JOURNAL OF MEDICINE

A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models

(2019) Evangelia Christodoulou et al.   JOURNAL OF CLINICAL EPIDEMIOLOGY

Validation of a Machine Learning Model That Outperforms Clinical Risk Scoring Systems for Upper Gastrointestinal Bleeding

(2019) Dennis L. Shung et al.   GASTROENTEROLOGY

Mortality Prediction of Septic Patients in the Emergency Department Based on Machine Learning

(2019) Jau-Woei Perng et al.   Journal of Clinical Medicine

Machine learning approaches for predicting disposition of asthma and COPD exacerbations in the ED

(2018) Tadahiro Goto et al.   AMERICAN JOURNAL OF EMERGENCY MEDICINE

Machine-Learning-Based Electronic Triage More Accurately Differentiates Patients With Respect to Clinical Outcomes Compared With the Emergency Severity Index

(2018) Scott Levin et al.   ANNALS OF EMERGENCY MEDICINE

Predicting urinary tract infections in the emergency department with machine learning

(2018) R. Andrew Taylor et al.   PLoS One

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

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

Dermatologist-level classification of skin cancer with deep neural networks

(2017) Andre Esteva et al.   NATURE

Natural and Artificial Intelligence in Neurosurgery: A Systematic Review

(2017) Joeky T Senders et al.   NEUROSURGERY

A guide to systematic review and meta-analysis of prediction model performance

(2017) Thomas P A Debray et al.   BMJ-British Medical Journal

A guide to systematic review and meta-analysis of prediction model performance

(2017) Thomas P A Debray et al.   BMJ-British Medical Journal

Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach

(2016) R. Andrew Taylor et al.   ACADEMIC EMERGENCY 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

Assessment of Clinical Criteria for Sepsis

(2016) Christopher W. Seymour et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

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

(2015) Gary S. Collins et al.   ANNALS OF INTERNAL MEDICINE

The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets

(2015) Takaya Saito et al.   PLoS One

A Systematic Review of Studies Comparing Diagnostic Clinical Prediction Rules with Clinical Judgment

(2015) Sharon Sanders 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

Reporting and Methods in Clinical Prediction Research: A Systematic Review

(2012) Walter Bouwmeester et al.   PLOS MEDICINE

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

(2009) David Moher et al.   PLOS MEDICINE