Comparison of machine learning and logistic regression models in predicting acute kidney injury: A systematic review and meta-analysis

Logistic regression was as good as machine learning for predicting major chronic diseases

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Developing prediction models for clinical use using logistic regression: an overview

(2019) Maren E. Shipe et al.   Journal of Thoracic Disease

Early prediction of acute kidney injury following ICU admission using a multivariate panel of physiological measurements

(2019) Lindsay P. Zimmerman et al.   BMC Medical Informatics and Decision Making

Automated Continuous Acute Kidney Injury Prediction and Surveillance: A Random Forest Model

(2019) Caitlyn Chiofolo et al.   MAYO CLINIC PROCEEDINGS

Artificial intelligence and machine learning for predicting acute kidney injury in severely burned patients: A proof of concept

(2019) Nam K. Tran et al.   BURNS

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

A clinically applicable approach to continuous prediction of future acute kidney injury

(2019) Nenad Tomašev et al.   NATURE

Improved predictive models for acute kidney injury with IDEA: Intraoperative Data Embedded Analytics

(2019) Lasith Adhikari et al.   PLoS One

Machine learning for the prediction of acute kidney injury and paraplegia after thoracoabdominal aortic aneurysm repair

(2019) Chenyang Zhou et al.   JOURNAL OF CARDIAC SURGERY

The Development of a Machine Learning Inpatient Acute Kidney Injury Prediction Model*

(2018) Jay L. Koyner et al.   CRITICAL CARE MEDICINE

EGBMMDA: Extreme Gradient Boosting Machine for MiRNA-Disease Association prediction

(2018) Xing Chen et al.   Cell Death & Disease

Trends in Hospitalizations for Acute Kidney Injury — United States, 2000–2014

(2018) Meda E. Pavkov et al.   MMWR-MORBIDITY AND MORTALITY WEEKLY REPORT

A clinical, proteomics, and artificial intelligence-driven model to predict acute kidney injury in patients undergoing coronary angiography

(2018) Nasrien E. Ibrahim et al.   CLINICAL CARDIOLOGY

Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study

(2018) Chenxi Huang et al.   PLOS MEDICINE

AKIpredictor, an online prognostic calculator for acute kidney injury in adult critically ill patients: development, validation and comparison to serum neutrophil gelatinase-associated lipocalin

(2017) Marine Flechet et al.   INTENSIVE CARE MEDICINE

Calibration drift in regression and machine learning models for acute kidney injury

(2017) Sharon E Davis et al.   JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION

Prediction and detection models for acute kidney injury in hospitalized older adults

(2016) Rohit J. Kate et al.   BMC Medical Informatics and Decision Making

Identification of Diagnostic Urinary Biomarkers for Acute Kidney Injury

(2016) Sanju A. Varghese et al.   JOURNAL OF INVESTIGATIVE MEDICINE

Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications

(2016) Paul Thottakkara et al.   PLoS One

National Veterans Health Administration inpatient risk stratification models for hospital-acquired acute kidney injury

(2015) Robert M Cronin et al.   JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION