AIMC Topic: Mortality
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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...
Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker.
Nature aging
Jun 24, 2024
Short-term mortality risk, which is indicative of individual frailty, serves as a marker for aging. Previous age clocks focused on predicting either chronological age or longer-term mortality. Aging clocks predicting short-term mortality are lacking ...
Machine learning prediction of one-year mortality after percutaneous coronary intervention in acute coronary syndrome patients.
International journal of cardiology
May 20, 2024
BACKGROUND: Machine learning (ML) models have the potential to accurately predict outcomes and offer novel insights into inter-variable correlations. In this study, we aimed to design ML models for the prediction of 1-year mortality after percutaneou...
Towards proactive palliative care in oncology: developing an explainable EHR-based machine learning model for mortality risk prediction.
BMC palliative care
May 20, 2024
BACKGROUND: Ex-ante identification of the last year in life facilitates a proactive palliative approach. Machine learning models trained on electronic health records (EHR) demonstrate promising performance in cancer prognostication. However, gaps in ...
Self-Supervised Machine Learning to Characterize Step Counts from Wrist-Worn Accelerometers in the UK Biobank.
Medicine and science in sports and exercise
May 15, 2024
PURPOSE: Step count is an intuitive measure of physical activity frequently quantified in health-related studies; however, accurate step counting is difficult in the free-living environment, with error routinely above 20% in wrist-worn devices agains...
Physical performance strongly predicts all-cause mortality risk in a real-world population of older diabetic patients: machine learning approach for mortality risk stratification.
Frontiers in endocrinology
Apr 30, 2024
BACKGROUND: Prognostic risk stratification in older adults with type 2 diabetes (T2D) is important for guiding decisions concerning advance care planning.
Looking Beyond Mortality Prediction: Primary Care Physician Views of Patients' Palliative Care Needs Predicted by a Machine Learning Tool.
Applied clinical informatics
Apr 18, 2024
OBJECTIVES: To assess primary care physicians' (PCPs) perception of the need for serious illness conversations (SIC) or other palliative care interventions in patients flagged by a machine learning tool for high 1-year mortality risk.
Development, validation, and transportability of several machine-learned, non-exercise-based VO prediction models for older adults.
Journal of sport and health science
Feb 29, 2024
BACKGROUND: There exist few maximal oxygen uptake (VO) non-exercise-based prediction equations, fewer using machine learning (ML), and none specifically for older adults. Since direct measurement of VO is infeasible in large epidemiologic cohort stud...
Comment on 'study and validation of an explainable machine learning-based mortality prediction following emergency surgery in the elderly: a prospective observational study'.
International journal of surgery (London, England)
Apr 1, 2023
Style-transfer counterfactual explanations: An application to mortality prevention of ICU patients.
Artificial intelligence in medicine
Nov 23, 2022
In recent years, machine learning methods have been rapidly adopted in the medical domain. However, current state-of-the-art medical mining methods usually produce opaque, black-box models. To address the lack of model transparency, substantial atten...
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