AIMC Topic: Mortality

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Precision Radiology: Predicting longevity using feature engineering and deep learning methods in a radiomics framework.

Scientific reports May 10, 2017
Precision medicine approaches rely on obtaining precise knowledge of the true state of health of an individual patient, which results from a combination of their genetic risks and environmental exposures. This approach is currently limited by the lac...
Longevity Precision Medicine Task Performance and Analysis Tomography, X-Ray Computed Kaplan-Meier Estimate Reproducibility of Results Mortality Humans Phenotype Image Processing, Computer-Assisted Area Under Curve Diagnostic Imaging Risk Factors Radiology Deep Learning ROC Curve
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Ensemble learning of inverse probability weights for marginal structural modeling in large observational datasets.

Statistics in medicine Oct 15, 2014
Inverse probability weights used to fit marginal structural models are typically estimated using logistic regression. However, a data-adaptive procedure may be able to better exploit information available in measured covariates. By combining predicti...
Confounding Factors, Epidemiologic Data Interpretation, Statistical Bias Antiretroviral Therapy, Highly Active HIV Infections Probability Spain Humans Logistic Models Confidence Intervals Machine Learning Mortality Models, Statistical Computer Simulation
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A novel metabolomic aging score - better than conventional metrics in predicting short-term mortality.

Expert review of molecular diagnostics Jul 1, 2025
INTRODUCTION: Accurate prediction of short-term mortality is crucial for optimizing clinical prognosis and providing treatment decisions. Conventional metrics, including physiological indicators, laboratory indexes and scoring systems, suffer from li...
Humans Biomarkers Prognosis Metabolome Mortality Aging Metabolomics
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External validation of a proprietary risk model for 1-year mortality in community-dwelling adults aged 65 years or older.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2025
OBJECTIVE: To examine the discrimination, calibration, and algorithmic fairness of the Epic End of Life Care Index (EOL-CI).
Female Aged Terminal Care Aged, 80 and over Risk Assessment Mortality Humans Male Independent Living ROC Curve Machine Learning Southeastern United States Area Under Curve Algorithms
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Recovering missing electronic health record mortality data with a machine learning-enhanced data linkage process.

Journal of the American Medical Informatics Association : JAMIA Jun 1, 2025
OBJECTIVE: To develop a continual process for linking more comprehensive external mortality data to electronic health records (EHRs) for a large healthcare system, which can serve as a template for other healthcare systems.
Humans Medical Record Linkage Machine Learning Mortality Electronic Health Records Death Certificates Information Storage and Retrieval
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Mortality risk assessment using deep learning-based frequency analysis of electroencephalography and electrooculography in sleep.

Sleep Feb 10, 2025
STUDY OBJECTIVES: To assess whether the frequency content of electroencephalography (EEG) and electrooculography (EOG) during nocturnal polysomnography (PSG) can predict all-cause mortality.
Mortality Polysomnography Electrooculography Risk Assessment Deep Learning Electroencephalography Sleep Stages Humans Female Male Middle Aged Aged Adult
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Transfer learning for mortality risk: A case study on the United Kingdom.

PloS one Jan 1, 2025
This study introduces a transfer learning framework to address data scarcity in mortality risk prediction for the UK, where local mortality data is unavailable. By leveraging a pretrained model built from data across eight countries (excluding the UK...
Risk Assessment United Kingdom Mortality Humans Machine Learning
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Comparing Cadence vs. Machine Learning Based Physical Activity Intensity Classifications: Variations in the Associations of Physical Activity With Mortality.

Scandinavian journal of medicine & science in sports Sep 1, 2024
Step cadence-based and machine-learning (ML) methods have been used to classify physical activity (PA) intensity in health-related research. This study examined the association of intensity-specific PA duration with all-cause (ACM) and CVD mortality ...
Mortality Walking United Kingdom Accelerometry Cardiovascular Diseases Middle Aged Exercise Humans Machine Learning Female Aged Adult Male
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A deep learning model accurately predicts 1-year mortality but at the risk of unfairness.

Nature aging Jul 1, 2024
Mortality Humans Aged Female Male Deep Learning
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Long-term mortality burden trends attributed to black carbon and PM from wildfire emissions across the continental USA from 2000 to 2020: a deep learning modelling study.

The Lancet. Planetary health Dec 1, 2023
BACKGROUND: Long-term improvements in air quality and public health in the continental USA were disrupted over the past decade by increased fire emissions that potentially offset the decrease in anthropogenic emissions. This study aims to estimate tr...
Cohort Studies United States Carbon Wildfires Mortality Air Pollutants Particulate Matter Humans Deep Learning Soot
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