AIMC Topic: Mortality

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A Real-Time Early Warning System for Monitoring Inpatient Mortality Risk: Prospective Study Using Electronic Medical Record Data.

Journal of medical Internet research
BACKGROUND: The rapid deterioration observed in the condition of some hospitalized patients can be attributed to either disease progression or imperfect triage and level of care assignment after their admission. An early warning system (EWS) to ident...

Can AI Help Reduce Disparities in General Medical and Mental Health Care?

AMA journal of ethics
BACKGROUND: As machine learning becomes increasingly common in health care applications, concerns have been raised about bias in these systems' data, algorithms, and recommendations. Simply put, as health care improves for some, it might not improve ...

Prediction of mortality following pediatric heart transplant using machine learning algorithms.

Pediatric transplantation
BACKGROUND: Optimizing transplant candidates' priority for donor organs depends on the accurate assessment of post-transplant outcomes. Due to the complexity of transplantation and the wide range of possible serious complications, recipient outcomes ...

Comparison of machine learning techniques to predict all-cause mortality using fitness data: the Henry ford exercIse testing (FIT) project.

BMC medical informatics and decision making
BACKGROUND: Prior studies have demonstrated that cardiorespiratory fitness (CRF) is a strong marker of cardiovascular health. Machine learning (ML) can enhance the prediction of outcomes through classification techniques that classify the data into p...

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

Scientific reports
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...

Ensemble learning of inverse probability weights for marginal structural modeling in large observational datasets.

Statistics in medicine
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...

A novel metabolomic aging score - better than conventional metrics in predicting short-term mortality.

Expert review of molecular diagnostics
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...

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
OBJECTIVE: To examine the discrimination, calibration, and algorithmic fairness of the Epic End of Life Care Index (EOL-CI).

Recovering missing electronic health record mortality data with a machine learning-enhanced data linkage process.

Journal of the American Medical Informatics Association : JAMIA
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.