AIMC Topic: Hospital Mortality

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A machine learning-based predictive model for the in-hospital mortality of critically ill patients with atrial fibrillation.

International journal of medical informatics Jul 31, 2024
BACKGROUND: Atrial fibrillation (AF) is common among intensive care unit (ICU) patients and significantly raises the in-hospital mortality rate. Existing scoring systems or models have limited predictive capabilities for AF patients in ICU. Our study...
Humans Critical Illness Female Reproducibility of Results Machine Learning Computer Simulation Hospital Mortality Aged Atrial Fibrillation Aged, 80 and over Male Risk Assessment
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A Machine Learning Model for Predicting In-Hospital Mortality in Chinese Patients With ST-Segment Elevation Myocardial Infarction: Findings From the China Myocardial Infarction Registry.

Journal of medical Internet research Jul 30, 2024
BACKGROUND: Machine learning (ML) risk prediction models, although much more accurate than traditional statistical methods, are inconvenient to use in clinical practice due to their nontransparency and requirement of a large number of input variables...
East Asian People ST Elevation Myocardial Infarction Registries Myocardial Infarction Male Middle Aged China Hospital Mortality Machine Learning Retrospective Studies Female Aged Humans
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Evaluating the effectiveness of a sliding window technique in machine learning models for mortality prediction in ICU cardiac arrest patients.

International journal of medical informatics Jul 27, 2024
Extensive research has been devoted to predicting ICU mortality, to assist clinical teams managing critical patients. Electronic health records (EHR) contain both static and dynamic medical data, with the latter accumulating during ICU stays. Existin...
Intensive Care Units Electronic Health Records Female Aged Hospital Mortality Humans Heart Arrest Male Machine Learning Middle Aged
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Machine learning models including preoperative and postoperative albumin-bilirubin score: short-term outcomes among patients with hepatocellular carcinoma.

HPB : the official journal of the International Hepato Pancreato Biliary Association Jul 25, 2024
BACKGROUND: We sought to assess the impact of various perioperative factors on the risk of severe complications and post-surgical mortality using a novel maching learning technique.
Hepatectomy Serum Albumin, Human Serum Albumin Carcinoma, Hepatocellular Treatment Outcome Predictive Value of Tests Bilirubin Postoperative Complications Time Factors Hospital Mortality Liver Neoplasms Humans Risk Factors Male Machine Learning Aged Middle Aged Databases, Factual Risk Assessment Retrospective Studies Female
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Cluster analysis of thoracic muscle mass using artificial intelligence in severe pneumonia.

Scientific reports Jul 23, 2024
Severe pneumonia results in high morbidity and mortality despite advanced treatments. This study investigates thoracic muscle mass from chest CT scans as a biomarker for predicting clinical outcomes in ICU patients with severe pneumonia. Analyzing el...
Middle Aged Hospital Mortality Cluster Analysis Pneumonia Intensive Care Units Female Aged Male Community-Acquired Infections Humans Artificial Intelligence Prognosis Tomography, X-Ray Computed
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Development of machine learning models predicting mortality using routinely collected observational health data from 0-59 months old children admitted to an intensive care unit in Bangladesh: critical role of biochemistry and haematology data.

BMJ paediatrics open Jul 22, 2024
INTRODUCTION: Treatment in the intensive care unit (ICU) generates complex data where machine learning (ML) modelling could be beneficial. Using routine hospital data, we evaluated the ability of multiple ML models to predict inpatient mortality in a...
Intensive Care Units Female Infant, Newborn Male Infant Humans Machine Learning Retrospective Studies Child, Preschool Hospital Mortality ROC Curve Bangladesh
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ICURE: Intensive care unit (ICU) risk evaluation for 30-day mortality. Developing and evaluating a multivariable machine learning prediction model for patients admitted to the general ICU in Sweden.

Acta anaesthesiologica Scandinavica Jul 21, 2024
BACKGROUND: A prediction model that estimates mortality at admission to the intensive care unit (ICU) is of potential benefit to both patients and society. Logistic regression models like Simplified Acute Physiology Score 3 (SAPS 3) and APACHE are th...
Registries Simplified Acute Physiology Score Sweden Aged Aged, 80 and over Adult Risk Assessment Hospital Mortality Logistic Models Humans Male Machine Learning Middle Aged Intensive Care Units Female
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Prediction of in-hospital Mortality of Intensive Care Unit Patients with Acute Pancreatitis Based on an Explainable Machine Learning Algorithm.

Journal of clinical gastroenterology Jul 1, 2024
BACKGROUND AND AIM: Acute pancreatitis (AP) is potentially fatal. Therefore, early identification of patients at a high mortality risk and timely intervention are essential. This study aimed to establish an explainable machine-learning model for pred...
Algorithms Intensive Care Units Female Aged Humans Machine Learning Severity of Illness Index Adult ROC Curve Hospital Mortality Male Bayes Theorem Middle Aged Pancreatitis Risk Assessment
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Machine learning for the prediction of in-hospital mortality in patients with spontaneous intracerebral hemorrhage in intensive care unit.

Scientific reports Jun 20, 2024
This study aimed to develop a machine learning (ML)-based tool for early and accurate prediction of in-hospital mortality risk in patients with spontaneous intracerebral hemorrhage (sICH) in the intensive care unit (ICU). We did a retrospective study...
Intensive Care Units Middle Aged Hospital Mortality Female Cerebral Hemorrhage Aged Humans Male Machine Learning Prognosis Retrospective Studies
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Machine-learning clustering analysis identifies novel phenogroups in patients with ST-elevation acute myocardial infarction.

International journal of cardiology Jun 15, 2024
BACKGROUND: Machine learning clustering of patients with ST-elevation acute myocardial infarction (STEMI) may provide important insights into their risk profile, management and prognosis.
Hospital Mortality Humans Cluster Analysis Machine Learning ST Elevation Myocardial Infarction Prognosis Aged Female Adult Risk Factors Male Middle Aged
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