AIMC Topic: APACHE
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A Racially Unbiased, Machine Learning Approach to Prediction of Mortality: Algorithm Development Study.
JMIR public health and surveillance
Oct 22, 2020
BACKGROUND: Racial disparities in health care are well documented in the United States. As machine learning methods become more common in health care settings, it is important to ensure that these methods do not contribute to racial disparities throu...
Development of Machine Learning Models to Validate a Medication Regimen Complexity Scoring Tool for Critically Ill Patients.
The Annals of pharmacotherapy
Sep 15, 2020
INTRODUCTION: The Medication Regimen Complexity -Intensive Care Unit (MRC-ICU) is the first tool for measuring medication regimen complexity in critically ill patients. This study tested machine learning (ML) models to investigate the relationship be...
Utilization of machine-learning models to accurately predict the risk for critical COVID-19.
Internal and emergency medicine
Aug 18, 2020
Among patients with Coronavirus disease (COVID-19), the ability to identify patients at risk for deterioration during their hospital stay is essential for effective patient allocation and management. To predict patient risk for critical COVID-19 base...
Prediction of mortality in Intensive Care Units: a multivariate feature selection.
Journal of biomedical informatics
May 23, 2020
CONTEXT: The critical nature of patients in Intensive Care Units (ICUs) demands intensive monitoring of their vital signs as well as highly qualified professional assistance. The combination of these needs makes ICUs very expensive, which requires in...
Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy.
Critical care (London, England)
Feb 6, 2020
BACKGROUND: Previous scoring models such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) and the Sequential Organ Failure Assessment (SOFA) scoring systems do not adequately predict mortality of patients undergoing co...
Usefulness of presepsin as diagnostic and prognostic marker of sepsis in daily clinical practice.
Journal of infection in developing countries
Nov 30, 2019
INTRODUCTION: Sepsis represents a major cause of morbidity and mortality in critically ill patients. Early diagnosis and appropriate treatment have a crucial influence on survival. The aim of this study was to evaluate the diagnostic and prognostic r...
Artificial neural networks accurately predict intra-abdominal infection in moderately severe and severe acute pancreatitis.
Journal of digestive diseases
Jul 21, 2019
OBJECTIVE: The aim of this study was to evaluate the efficacy of artificial neural networks (ANN) in predicting intra-abdominal infection in moderately severe (MASP) and severe acute pancreatitis (SAP) compared with that of a logistic regression mode...
Development and validation of three machine-learning models for predicting multiple organ failure in moderately severe and severe acute pancreatitis.
BMC gastroenterology
Jul 4, 2019
BACKGROUND: Multiple organ failure (MOF) is a serious complication of moderately severe (MASP) and severe acute pancreatitis (SAP). This study aimed to develop and assess three machine-learning models to predict MOF.
An intelligent warning model for early prediction of cardiac arrest in sepsis patients.
Computer methods and programs in biomedicine
Jun 11, 2019
BACKGROUND: Sepsis-associated cardiac arrest is a common issue with the low survival rate. Early prediction of cardiac arrest can provide the time required for intervening and preventing its onset in order to reduce mortality. Several studies have be...
Normal Distribution
Heart Arrest
Decision Trees
Monitoring, Ambulatory
APACHE
Multivariate Analysis
Vital Signs
Severity of Illness Index
Case-Control Studies
Sepsis
Adolescent
Incidence
Humans
Young Adult
Adult
Sensitivity and Specificity
Male
Middle Aged
Machine Learning
Algorithms
Electronic Health Records
Female
Reproducibility of Results
Comparison of machine learning models for the prediction of mortality of patients with unplanned extubation in intensive care units.
Scientific reports
Nov 20, 2018
Unplanned extubation (UE) can be associated with fatal outcome; however, an accurate model for predicting the mortality of UE patients in intensive care units (ICU) is lacking. Therefore, we aim to compare the performances of various machine learning...
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