AIMC Topic: Mortality
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Enhanced machine learning models for predicting three-year mortality in Non-STEMI patients aged 75 and above.
BMC geriatrics
Jul 2, 2025
BACKGROUND: Non-ST segment elevation myocardial infarction (Non-STEMI) is a severe cardiovascular condition mainly affecting individuals aged 75 and above, who are at higher risk of mortality due to age-related vulnerabilities and other health issues...
AI-based volumetric six-tissue body composition quantification from CT cardiac attenuation scans for mortality prediction: a multicentre study.
The Lancet. Digital health
May 16, 2025
BACKGROUND: CT attenuation correction (CTAC) scans are routinely obtained during cardiac perfusion imaging, but currently only used for attenuation correction and visual calcium estimation. We aimed to develop a novel artificial intelligence (AI)-bas...
Spatiotemporal evolution and risk thresholds of PM components in China from the human health perspective.
Environmental pollution (Barking, Essex : 1987)
Apr 2, 2025
PM is a significant global public health hazard, with its components closely linked to various fatal diseases, thereby significantly increasing mortality rates. This study analysed the spatiotemporal evolution of PM-related mortality and death rates ...
The association of lifestyle with cardiovascular and all-cause mortality based on machine learning: a prospective study from the NHANES.
BMC public health
Jan 24, 2025
BACKGROUND: Lifestyle and cardiovascular mortality and all-cause mortality have been exhaustively explored by traditional methods, but the advantages of machine learning (ML) over traditional methods may lead to different or more precise conclusions....
Application of machine learning algorithms in an epidemiologic study of mortality.
Annals of epidemiology
Jan 3, 2025
PURPOSE: Epidemiologic studies are important in assessing risk factors of mortality. Machine learning (ML) is efficient in analyzing multidimensional data to unravel dependencies between risk factors and health outcomes.
Data-driven insights into pre-slaughter mortality: Machine learning for predicting high dead on arrival in meat-type ducks.
Poultry science
Dec 6, 2024
Dead on arrival (DOA) refers to animals, particularly poultry, that die during the pre-slaughter phase. Elevated rates of DOA frequently signify substandard welfare conditions and might stem from multiple causes, resulting in diminished productivity ...
Metabolomics-Based Machine Learning for Predicting Mortality: Unveiling Multisystem Impacts on Health.
International journal of molecular sciences
Oct 30, 2024
Reliable predictors of long-term all-cause mortality are needed for middle-aged and older populations. Previous metabolomics mortality studies have limitations: a low number of participants and metabolites measured, measurements mainly using nuclear ...
Application of a deep-learning marker for morbidity and mortality prediction derived from retinal photographs: a cohort development and validation study.
The lancet. Healthy longevity
Sep 30, 2024
BACKGROUND: Biological ageing markers are useful to risk stratify morbidity and mortality more precisely than chronological age. In this study, we aimed to develop a novel deep-learning-based biological ageing marker (referred to as RetiPhenoAge here...
Reconfiguration of uncertainty: Introducing AI for prediction of mortality at the emergency department.
Social science & medicine (1982)
Sep 6, 2024
The promise behind many advanced digital technologies in healthcare is to provide novel and accurate information, aiding medical experts to navigate and, ultimately, decrease uncertainty in their clinical work. However, sociological studies have star...
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...
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