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Clinical Decision Rules

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Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study.

Journal of diabetes research 32626780
BACKGROUND: Gestational diabetes mellitus (GDM) contributes to adverse pregnancy and birth outcomes. In recent decades, extensive research has been devoted to the early prediction of GDM by various methods. Machine learning methods are flexible predi...
Adult Blood Glucose Cholesterol Clinical Decision Rules Cohort Studies Decision Trees Diabetes, Gestational Female Glycated Hemoglobin Humans Lipoproteins, HDL Logistic Models Machine Learning Maternal Age Pregnancy Pregnancy in Obesity Reproducibility of Results Retrospective Studies Routinely Collected Health Data Triglycerides Uric Acid Young Adult
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Benchmarking machine learning models on multi-centre eICU critical care dataset.

PloS one 32614874
Progress of machine learning in critical care has been difficult to track, in part due to absence of public benchmarks. Other fields of research (such as computer vision and natural language processing) have established various competitions and publi...
Algorithms Benchmarking Clinical Decision Rules Critical Care Datasets as Topic Hospital Mortality Humans Length of Stay Machine Learning Software
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Evaluation of a Machine Learning Model Based on Pretreatment Symptoms and Electroencephalographic Features to Predict Outcomes of Antidepressant Treatment in Adults With Depression: A Prespecified Secondary Analysis of a Randomized Clinical Trial.

JAMA network open 32568399
IMPORTANCE: Despite the high prevalence and potential outcomes of major depressive disorder, whether and how patients will respond to antidepressant medications is not easily predicted.
Adult Algorithms Antidepressive Agents Citalopram Clinical Decision Rules Depressive Disorder, Major Electroencephalography Female Humans Machine Learning Male Middle Aged Prognosis Prospective Studies Sertraline Treatment Outcome Venlafaxine Hydrochloride
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Clinical applications of machine learning in the diagnosis, classification, and prediction of heart failure.

American heart journal 32905873
Machine learning and artificial intelligence are generating significant attention in the scientific community and media. Such algorithms have great potential in medicine for personalizing and improving patient care, including in the diagnosis and man...
Clinical Decision Rules Heart Failure Humans Machine Learning Prognosis
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Early Prediction of Acute Kidney Injury in the Emergency Department With Machine-Learning Methods Applied to Electronic Health Record Data.

Annals of emergency medicine 32713624
STUDY OBJECTIVE: Acute kidney injury occurs commonly and is a leading cause of prolonged hospitalization, development and progression of chronic kidney disease, and death. Early acute kidney injury treatment can improve outcomes. However, current dec...
Acute Kidney Injury Adolescent Adult Aged Aged, 80 and over Clinical Decision Rules Creatinine Cross-Sectional Studies Electronic Health Records Emergency Service, Hospital Female Humans Machine Learning Male Middle Aged Retrospective Studies
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Development and Validation of Machine Learning-Based Prediction for Dependence in the Activities of Daily Living after Stroke Inpatient Rehabilitation: A Decision-Tree Analysis.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association 32992179
BACKGROUND AND PURPOSE: Accurate prediction using simple and changeable variables is clinically meaningful because some known-predictors, such as stroke severity and patients age cannot be modified with rehabilitative treatment. There are limited cli...
Activities of Daily Living Aged Aged, 80 and over Clinical Decision Rules Databases, Factual Decision Trees Female Humans Inpatients Machine Learning Male Middle Aged Mobility Limitation Predictive Value of Tests Recovery of Function Reproducibility of Results Risk Assessment Risk Factors Stroke Stroke Rehabilitation Treatment Outcome
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Prediction of obstetrical and fetal complications using automated electronic health record data.

American journal of obstetrics and gynecology 33098815
An increasing number of delivering women experience major morbidity and mortality. Limited work has been done on automated predictive models that could be used for prevention. Using only routinely collected obstetrical data, this study aimed to devel...
Adult Blood Pressure Clinical Decision Rules Electronic Health Records Female Humans Hypoxia-Ischemia, Brain Machine Learning Maternal Age Obstetric Labor Complications Parity Postpartum Hemorrhage Pre-Eclampsia Pregnancy Pregnancy in Obesity Premature Birth Reproducibility of Results Retrospective Studies Routinely Collected Health Data Stillbirth Time Factors Uterine Rupture
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CORR Synthesis: When Should We Be Skeptical of Clinical Prediction Models?

Clinical orthopaedics and related research 32667756
Artificial Intelligence Checklist Clinical Decision Rules Clinical Decision-Making Humans Machine Learning Nomograms Reproducibility of Results Risk Assessment Risk Factors
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Early identification of patients with acute gastrointestinal bleeding using natural language processing and decision rules.

Journal of gastroenterology and hepatology 33105045
BACKGROUND AND AIM: Guidelines recommend risk stratification scores in patients presenting with gastrointestinal bleeding (GIB), but such scores are uncommonly employed in practice. Automation and deployment of risk stratification scores in real time...
Acute Disease Algorithms Clinical Decision Rules Early Diagnosis Electronic Health Records Emergency Service, Hospital Female Gastrointestinal Hemorrhage Humans Male Middle Aged Natural Language Processing Risk Assessment Triage
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Low Predictability of Readmissions and Death Using Machine Learning in Cirrhosis.

The American journal of gastroenterology 33038139
INTRODUCTION: Readmission and death in cirrhosis are common, expensive, and difficult to predict. Our aim was to evaluate the abilities of multiple artificial intelligence (AI) techniques to predict clinical outcomes based on variables collected at a...
Adrenergic beta-Antagonists Aged Anti-Bacterial Agents Ascites beta-Lactams Clinical Decision Rules Cohort Studies End Stage Liver Disease Female Gastrointestinal Agents Gastrointestinal Hemorrhage Hepatic Encephalopathy Humans Hydrothorax Infections Kidney Diseases Lactulose Liver Cirrhosis Logistic Models Machine Learning Male Middle Aged Mortality Paracentesis Patient Readmission Proton Pump Inhibitors Reproducibility of Results Rifaximin ROC Curve Severity of Illness Index Support Vector Machine Water-Electrolyte Imbalance
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