AIMC Topic: Mortality

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Detection of the Relationship between the Multi-Dimensional Data Sets of Serially Measured Blood Pressure and the Future Risk of Death in Healthy Elderly Japanese Population.

Journal of atherosclerosis and thrombosis Oct 21, 2022
AIMS: Whether the multi-dimensional data of serially measured blood pressure contains information for predicting the future risk of death in elderly individuals in nursing homes is unclear.
Artificial Intelligence Aged East Asian People Blood Pressure Mortality Humans Neural Networks, Computer
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Prediction algorithm for ICU mortality and length of stay using machine learning.

Scientific reports Jul 28, 2022
Machine learning can predict outcomes and determine variables contributing to precise prediction, and can thus classify patients with different risk factors of outcomes. This study aimed to investigate the predictive accuracy for mortality and length...
Machine Learning Algorithms Retrospective Studies Intensive Care Units Length of Stay Humans Area Under Curve Mortality
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Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study.

Scientific reports Nov 26, 2021
We present a simple and efficient hypothesis-free machine learning pipeline for risk factor discovery that accounts for non-linearity and interaction in large biomedical databases with minimal variable pre-processing. In this study, mortality models ...
Smoking Life Style Mortality Databases, Factual Female Humans Risk Factors Machine Learning Aged Male Middle Aged Cohort Studies United Kingdom Cognition Disorders
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Prediction Model Using Machine Learning for Mortality in Patients with Heart Failure.

The American journal of cardiology Jul 7, 2021
Heart Failure (HF) is a major cause of morbidity and mortality in the US. With aging of the US population, the public health burden of HF is enormous. We aimed to develop an ensemble prediction model for 30-day mortality after discharge using machine...
Machine Learning Female Hospitalization Aged Aged, 80 and over Humans Mortality Clinical Decision Rules Male Middle Aged Cause of Death Heart Failure
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Application of machine learning approaches to administrative claims data to predict clinical outcomes in medical and surgical patient populations.

PloS one Jun 3, 2021
OBJECTIVE: This study aimed to develop and validate a claims-based, machine learning algorithm to predict clinical outcomes across both medical and surgical patient populations.
Machine Learning Databases, Factual Retrospective Studies Hospitalization Risk Assessment Humans Treatment Outcome Area Under Curve Medicare Mortality ROC Curve Logistic Models United States Models, Theoretical
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Prediction and Feature Importance Analysis for Severity of COVID-19 in South Korea Using Artificial Intelligence: Model Development and Validation.

Journal of medical Internet research Apr 19, 2021
BACKGROUND: The number of deaths from COVID-19 continues to surge worldwide. In particular, if a patient's condition is sufficiently severe to require invasive ventilation, it is more likely to lead to death than to recovery.
Male Middle Aged Infant Adolescent Child, Preschool Aged Aged, 80 and over Young Adult Adult Child Models, Statistical Mortality Humans Republic of Korea Female Infant, Newborn SARS-CoV-2 Risk Factors Artificial Intelligence COVID-19 Research Design Retrospective Studies
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Predictors of 30-Day Mortality Among Dutch Patients Undergoing Colorectal Cancer Surgery, 2011-2016.

JAMA network open Apr 1, 2021
IMPORTANCE: Quality improvement programs for colorectal cancer surgery have been introduced with benchmarking based on quality indicators, such as mortality. Detailed (pre)operative characteristics may offer relevant information for proper case-mix c...
Colectomy Multivariate Analysis Mortality Laparoscopy Myocardial Infarction Netherlands Patient Readmission Colorectal Neoplasms Male Middle Aged Comorbidity Length of Stay Logistic Models Hypertension Support Vector Machine Risk Factors Area Under Curve Aged Humans Aged, 80 and over Machine Learning Pulmonary Disease, Chronic Obstructive Intensive Care Units Asthma Female
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A Clinically Practical and Interpretable Deep Model for ICU Mortality Prediction with External Validation.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Deep learning models are increasingly studied in the field of critical care. However, due to the lack of external validation and interpretability, it is difficult to generalize deep learning models in critical care senarios. Few works have validated ...
Mortality Humans Neural Networks, Computer Intensive Care Units Critical Care
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Logistic regression and machine learning predicted patient mortality from large sets of diagnosis codes comparably.

Journal of clinical epidemiology Jan 22, 2021
OBJECTIVE: The objective of the study was to compare the performance of logistic regression and boosted trees for predicting patient mortality from large sets of diagnosis codes in electronic healthcare records.
Middle Aged England Logistic Models Age Factors Myocardial Infarction Sex Factors Hip Fractures International Classification of Diseases Humans Mortality Aged Aged, 80 and over Colorectal Neoplasms Male Machine Learning Forecasting Electronic Health Records Female
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Machine learning to predict mortality after rehabilitation among patients with severe stroke.

Scientific reports Nov 18, 2020
Stroke is among the leading causes of death and disability worldwide. Approximately 20-25% of stroke survivors present severe disability, which is associated with increased mortality risk. Prognostication is inherent in the process of clinical decisi...
Medicare Clinical Decision-Making Mortality Female Humans Stroke Rehabilitation Aged Machine Learning Male Algorithms Middle Aged ROC Curve Logistic Models United States Stroke
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