AIMC Topic: Hospital Mortality

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Prediction of mortality in sepsis patients using stacked ensemble machine learning algorithm.

Journal of postgraduate medicine Dec 6, 2024
INTRODUCTION: Machine learning (ML) has been tried in predicting outcomes following sepsis. This study aims to identify the utility of stacked ensemble algorithm in predicting mortality.
Sepsis Female Cohort Studies Humans Aged Machine Learning Hospital Mortality Adult Algorithms Support Vector Machine Male Prognosis Area Under Curve Middle Aged
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Performance of machine learning versus the national early warning score for predicting patient deterioration risk: a single-site study of emergency admissions.

BMJ health & care informatics Dec 4, 2024
OBJECTIVES: Increasing operational pressures on emergency departments (ED) make it imperative to quickly and accurately identify patients requiring urgent clinical intervention. The widespread adoption of electronic health records (EHR) makes rich fe...
Machine Learning Retrospective Studies Electronic Health Records Female Aged Humans Early Warning Score Clinical Deterioration Hospital Mortality Triage Emergency Service, Hospital Adult United Kingdom Male Patient Admission Middle Aged Risk Assessment
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PREDICTING IN-HOSPITAL MORTALITY IN CRITICAL ORTHOPEDIC TRAUMA PATIENTS WITH SEPSIS USING MACHINE LEARNING MODELS.

Shock (Augusta, Ga.) Dec 3, 2024
Purpose: This study aims to establish and validate machine learning-based models to predict death in hospital among critical orthopedic trauma patients with sepsis or respiratory failure. Methods: This study collected 523 patients from the Medical In...
Male Middle Aged Sepsis Humans Hospital Mortality Machine Learning Wounds and Injuries Female Aged Adult
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Prognostic value of glycaemic variability for mortality in critically ill atrial fibrillation patients and mortality prediction model using machine learning.

Cardiovascular diabetology Nov 26, 2024
BACKGROUND: The burden of atrial fibrillation (AF) in the intensive care unit (ICU) remains heavy. Glycaemic control is important in the AF management. Glycaemic variability (GV), an emerging marker of glycaemic control, is associated with unfavourab...
Female Reproducibility of Results Risk Factors Aged Aged, 80 and over Humans Prognosis Male Hospital Mortality Machine Learning Retrospective Studies Middle Aged Predictive Value of Tests Decision Support Techniques Critical Illness Cause of Death Databases, Factual Intensive Care Units Risk Assessment Atrial Fibrillation Biomarkers Blood Glucose Glycemic Control Time Factors
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Predictive model of in-hospital mortality in liver cirrhosis patients with hyponatremia: an artificial neural network approach.

Scientific reports Nov 20, 2024
Hyponatremia can worsen the outcomes of patients with liver cirrhosis. However, it remains unclear about how to predict the risk of death in cirrhotic patients with hyponatremia. Patients with liver cirrhosis and hyponatremia were screened. Eligible ...
ROC Curve Liver Cirrhosis Hyponatremia Aged Male Middle Aged Severity of Illness Index Hospital Mortality Humans Neural Networks, Computer Prognosis Female
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Random Forest Prognostication of Survival and 6-Month Outcome in Pediatric Patients Following Decompressive Craniectomy for Traumatic Brain Injury.

World neurosurgery Nov 15, 2024
BACKGROUND: There is a dearth of literature regarding prognostic and predictive factors for outcome following pediatric decompressive craniectomy (DC) performed after traumatic brain injury (TBI). The aim of this study was to develop a random forest ...
Infant Adolescent Child, Preschool Child Hospital Mortality Treatment Outcome Brain Injuries, Traumatic Random Forest Glasgow Outcome Scale Decompressive Craniectomy Machine Learning Prognosis Retrospective Studies Female Male Humans
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Machine learning for predicting in-hospital mortality in elderly patients with heart failure combined with hypertension: a multicenter retrospective study.

Cardiovascular diabetology Nov 15, 2024
BACKGROUND: Heart failure combined with hypertension is a major contributor for elderly patients (≥ 65 years) to in-hospital mortality. However, there are very few models to predict in-hospital mortality in such elderly patients. We aimed to develop ...
Humans Machine Learning Decision Support Techniques Databases, Factual Prognosis Retrospective Studies Female Age Factors Risk Assessment Predictive Value of Tests China Heart Failure Time Factors Risk Factors Hospital Mortality Aged Hypertension Aged, 80 and over Male
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Machine learning adjusted sequential CUSUM-analyses are superior to cross-sectional analysis of excess mortality after surgery.

International journal of medical informatics Nov 9, 2024
BACKGROUND: The assessment of clinical outcome quality, particularly in surgery, is crucial for healthcare improvement. Traditional cross-sectional analyses often fall short in timely and systematic identification of clinical quality issues. This stu...
Severity of Illness Index Hospital Mortality Surgical Procedures, Operative Humans Machine Learning Algorithms Female Cross-Sectional Studies Male Postoperative Complications
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Leveraging machine learning to enhance postoperative risk assessment in coronary artery bypass grafting patients with unprotected left main disease: a retrospective cohort study.

International journal of surgery (London, England) Nov 1, 2024
BACKGROUND: Risk stratification for patients undergoing coronary artery bypass surgery (CABG) for left main coronary artery (LMCA) disease is essential for informed decision-making. This study explored the potential of machine learning (ML) methods t...
Risk Factors Aged Male Middle Aged Risk Assessment Humans Machine Learning Retrospective Studies Female Postoperative Complications Hospital Mortality Coronary Artery Disease Coronary Artery Bypass
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A Machine Learning-derived Risk Score Improves Prediction of Outcomes After LVAD Implantation: An Analysis of the INTERMACS Database.

Journal of cardiac failure Oct 31, 2024
BACKGROUND: Significant variability in outcomes after left ventricular assist device (LVAD) implantation emphasize the importance of accurately assessing patients' risk before surgery. This study assesses the Machine Learning Assessment of Risk and E...
Treatment Outcome Predictive Value of Tests Registries Heart Failure Heart-Assist Devices Male Humans Middle Aged Machine Learning Risk Assessment Databases, Factual Hospital Mortality Prognosis Retrospective Studies Female Risk Factors Aged
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