AIMC Topic: Cause of Death

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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 Biomarkers Prognosis Retrospective Studies Critical Illness Intensive Care Units Hospital Mortality Predictive Value of Tests Cause of Death Atrial Fibrillation Glycemic Control Male Middle Aged Risk Assessment Blood Glucose Time Factors Humans Machine Learning Decision Support Techniques Databases, Factual
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Machine learning and statistical models to predict all-cause mortality in type 2 diabetes: Results from the UK Biobank study.

Diabetes & metabolic syndrome Oct 5, 2024
AIMS: This study aims to compare the performance of contemporary machine learning models with statistical models in predicting all-cause mortality in patients with type 2 diabetes mellitus and to develop a user-friendly mortality risk prediction tool...
Cause of Death Biological Specimen Banks United Kingdom UK Biobank Middle Aged Diabetes Mellitus, Type 2 Follow-Up Studies Models, Statistical Humans Machine Learning Prospective Studies Female Prognosis Risk Factors Aged Survival Rate Male
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Interpretable machine learning models for the prediction of all-cause mortality and time to death in hemodialysis patients.

Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy Sep 26, 2024
INTRODUCTION: The elevated mortality and hospitalization rates among hemodialysis (HD) patients underscore the necessity for the development of accurate predictive tools. This study developed two models for predicting all-cause mortality and time to ...
Support Vector Machine Kidney Failure, Chronic Cause of Death Machine Learning Retrospective Studies Female Aged Male Middle Aged Renal Dialysis Cohort Studies Time Factors Logistic Models Humans
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Text mining of verbal autopsy narratives to extract mortality causes and most prevalent diseases using natural language processing.

PloS one Sep 19, 2024
Verbal autopsy (VA) narratives play a crucial role in understanding and documenting the causes of mortality, especially in regions lacking robust medical infrastructure. In this study, we propose a comprehensive approach to extract mortality causes a...
Natural Language Processing Humans Cause of Death Retrospective Studies Autopsy Prevalence Data Mining Narration
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Using machine learning methods to investigate the impact of age on the causes of death in patients with early intrahepatic cholangiocarcinoma who underwent surgery.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico Sep 11, 2024
BACKGROUND: The impact of age on the causes of death (CODs) in patients with early-stage intrahepatic cholangiocarcinoma (ICC) who had undergone surgery was analyzed in this study.
Retrospective Studies Female Aged Aged, 80 and over Adult Humans Machine Learning Bile Duct Neoplasms Cholangiocarcinoma Survival Rate Male Middle Aged Age Factors Cause of Death
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Association of N-terminal pro-B natriuretic peptide with all-cause mortality and cardiovascular mortality in obese and non-obese populations and the development of a machine learning prediction model: National Health and Nutrition Examination Survey (NHANES) 1999-2004.

Diabetes, obesity & metabolism Sep 6, 2024
AIMS: To explore the potential of N-terminal pro-B natriuretic peptide (NTproBNP) in identifying adverse outcomes, particularly cardiovascular adverse outcomes, in a population with obesity, and to establish a risk prediction model.
Humans Machine Learning Biomarkers Obesity Cardiovascular Diseases Predictive Value of Tests Middle Aged Peptide Fragments Risk Assessment Cause of Death Nutrition Surveys Natriuretic Peptide, Brain Female United States Proportional Hazards Models Aged Adult Male
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Causes of death in individuals with lifetime major depression: a comprehensive machine learning analysis from a community-based autopsy center.

BMC psychiatry Jul 24, 2024
BACKGROUND: Depression can be associated with increased mortality and morbidity, but no studies have investigated the specific causes of death based on autopsy reports. Autopsy studies can yield valuable and detailed information on pathological ailme...
Machine Learning Female Aged Autopsy Aged, 80 and over Humans Adult Male Middle Aged Depressive Disorder, Major Case-Control Studies Cause of Death
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Random survival forest for predicting the combined effects of multiple physiological risk factors on all-cause mortality.

Scientific reports Jul 6, 2024
Understanding the combined effects of risk factors on all-cause mortality is crucial for implementing effective risk stratification and designing targeted interventions, but such combined effects are understudied. We aim to use survival-tree based ma...
Cotinine Cause of Death Mortality Leukocyte Count Humans Middle Aged Risk Factors Risk Assessment Machine Learning Aged Biomarkers Blood Glucose Adult Female Nutrition Surveys Male Glomerular Filtration Rate
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External validation of a 2-year all-cause mortality prediction tool developed using machine learning in patients with stage 4-5 chronic kidney disease.

Journal of nephrology Jul 4, 2024
BACKGROUND: Chronic kidney disease (CKD) is associated with increased mortality. Individual mortality prediction could be of interest to improve individual clinical outcomes. Using an independent regional dataset, the aim of the present study was to ...
Humans Cause of Death Machine Learning Prognosis Female Reproducibility of Results Risk Factors Time Factors ROC Curve Renal Insufficiency, Chronic Predictive Value of Tests Area Under Curve Aged Male Middle Aged Risk Assessment Severity of Illness Index
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Deep learning model for the prediction of all-cause mortality among long term care people in China: a prospective cohort study.

Scientific reports Jun 25, 2024
This study aimed to develop a deep learning model to predict the risk stratification of all-cause death for older people with disability, providing guidance for long-term care plans. Based on the government-led long-term care insurance program in a p...
Persons with Disabilities Prospective Studies Prognosis Cause of Death Humans Aged, 80 and over Female Mortality Male Risk Factors Long-Term Care Risk Assessment Aged Deep Learning China
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