AIMC Topic: Hospital Mortality

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Clinical decision support for severe trauma patients: Machine learning based definition of a bundle of care for hemorrhagic shock and traumatic brain injury.

The journal of trauma and acute care surgery Jan 1, 2022
BACKGROUND: Deviation from guidelines is frequent in emergency situations, and this may lead to increased mortality. Probably because of time constraints, 55% is the greatest reported guidelines compliance rate in severe trauma patients. This study a...
Decision Support Systems, Clinical Guideline Adherence Brain Injuries, Traumatic Emergency Medical Services Female Adult Male Hospital Mortality Humans Practice Guidelines as Topic Machine Learning France Shock, Hemorrhagic Registries Trauma Severity Indices Patient Care Bundles Critical Care Quality Improvement
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Detecting Uncertainty of Mortality Prediction Using Confident Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Early mortality prediction is an actively researched problem that has led to the development of various severity scores and machine learning (ML) models for accurate and reliable detection of mortality in severely ill patients staying in intensive ca...
Hospital Mortality Humans Uncertainty Machine Learning Databases, Factual Intensive Care Units
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Interpretable Machine Learning Model for Early Prediction of Mortality in ICU Patients with Rhabdomyolysis.

Medicine and science in sports and exercise Sep 1, 2021
PURPOSE: Rhabdomyolysis (RM) is a complex set of clinical syndromes that involves the rapid dissolution of skeletal muscles. Mortality from RM is approximately 10%. This study aimed to develop an interpretable and generalizable model for early mortal...
Machine Learning Retrospective Studies Intensive Care Units Female Humans Middle Aged Hospital Mortality Aged Predictive Value of Tests Adult Rhabdomyolysis Male
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Trauma outcome predictor: An artificial intelligence interactive smartphone tool to predict outcomes in trauma patients.

The journal of trauma and acute care surgery Jul 1, 2021
BACKGROUND: Classic risk assessment tools often treat patients' risk factors as linear and additive. Clinical reality suggests that the presence of certain risk factors can alter the impact of other factors; in other words, risk modeling is not linea...
Emergencies Hospital Mortality Smartphone United States Male Middle Aged Risk Assessment Predictive Value of Tests Injury Severity Score Wounds, Penetrating Artificial Intelligence Decision Support Techniques Databases, Factual Wounds, Nonpenetrating Female Risk Factors Aged Adult Humans
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Continuous Prediction of Mortality in the PICU: A Recurrent Neural Network Model in a Single-Center Dataset.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Jun 1, 2021
OBJECTIVES: Develop, as a proof of concept, a recurrent neural network model using electronic medical records data capable of continuously assessing an individual child's risk of mortality throughout their ICU stay as a proxy measure of severity of i...
Hospital Mortality Intensive Care Units, Pediatric ROC Curve Humans Neural Networks, Computer Retrospective Studies Infant Child
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Use of Machine Learning Models to Predict Death After Acute Myocardial Infarction.

JAMA cardiology Jun 1, 2021
IMPORTANCE: Accurate prediction of adverse outcomes after acute myocardial infarction (AMI) can guide the triage of care services and shared decision-making, and novel methods hold promise for using existing data to generate additional insights.
United States Registries Myocardial Infarction Risk Assessment Cohort Studies Hospital Mortality Humans Machine Learning Female Aged Male
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Predicting in-hospital mortality in ICU patients with sepsis using gradient boosting decision tree.

Medicine May 14, 2021
Sepsis is a leading cause of mortality in the intensive care unit. Early prediction of sepsis can reduce the overall mortality rate and cost of sepsis treatment. Some studies have predicted mortality and development of sepsis using machine learning m...
Clinical Decision Rules Humans ROC Curve Machine Learning Logistic Models Algorithms Support Vector Machine Sepsis Decision Trees Young Adult Adolescent Adult Intensive Care Units Hospital Mortality Male Female Middle Aged Aged Aged, 80 and over
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Development and validation of a machine learning model to predict mortality risk in patients with COVID-19.

BMJ health & care informatics May 1, 2021
New York City quickly became an epicentre of the COVID-19 pandemic. An ability to triage patients was needed due to a sudden and massive increase in patients during the COVID-19 pandemic as healthcare providers incurred an exponential increase in wor...
Humans Machine Learning COVID-19 Algorithms Forecasting Risk Assessment Retrospective Studies Hospital Mortality SARS-CoV-2 New York City
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Predicting 2-Day Mortality of Thrombocytopenic Patients Based on Clinical Laboratory Data Using Machine Learning.

Medical care Mar 1, 2021
BACKGROUND: Clinical laboratories have traditionally used a single critical value for thrombocytopenic events. This system, however, could lead to inaccuracies and inefficiencies, causing alarm fatigue and compromised patient safety.
Thrombocytopenia Hospital Mortality Support Vector Machine Machine Learning Bayes Theorem Forecasting Female Humans Male Hospitalization Risk Assessment Length of Stay Time Factors
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Optimization of Genomic Classifiers for Clinical Deployment: Evaluation of Bayesian Optimization to Select Predictive Models of Acute Infection and In-Hospital Mortality.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2021
Acute infection, if not rapidly and accurately detected, can lead to sepsis, organ failure and even death. Current detection of acute infection as well as assessment of a patient's severity of illness are imperfect. Characterization of a patient's im...
Humans Genomics Machine Learning Computational Biology Hospital Mortality Bayes Theorem
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