AIMC Topic: Mortality

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Comparing Logistic Regression Models with Alternative Machine Learning Methods to Predict the Risk of Drug Intoxication Mortality.

International journal of environmental research and public health Jan 31, 2020
(1) Medical research has shown an increasing interest in machine learning, permitting massive multivariate data analysis. Thus, we developed drug intoxication mortality prediction models, and compared machine learning models and traditional logistic ...
Risk Assessment Logistic Models Area Under Curve Mortality Alcoholic Intoxication Neural Networks, Computer Machine Learning Republic of Korea
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Representation learning for clinical time series prediction tasks in electronic health records.

BMC medical informatics and decision making Dec 17, 2019
BACKGROUND: Electronic health records (EHRs) provide possibilities to improve patient care and facilitate clinical research. However, there are many challenges faced by the applications of EHRs, such as temporality, high dimensionality, sparseness, n...
Algorithms Forecasting Electronic Health Records Comorbidity China Humans Neural Networks, Computer Machine Learning Heart Failure Mortality
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A deep learning model for real-time mortality prediction in critically ill children.

Critical care (London, England) Aug 14, 2019
BACKGROUND: The rapid development in big data analytics and the data-rich environment of intensive care units together provide unprecedented opportunities for medical breakthroughs in the field of critical care. We developed and validated a machine l...
Retrospective Studies Critical Illness Republic of Korea Female Male Humans Cohort Studies Child, Preschool Child ROC Curve Area Under Curve Risk Assessment Infant Deep Learning Big Data Adolescent Pediatrics Mortality
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Training machine learning models to predict 30-day mortality in patients discharged from the emergency department: a retrospective, population-based registry study.

BMJ open Aug 10, 2019
OBJECTIVES: The aim of this work was to train machine learning models to identify patients at end of life with clinically meaningful diagnostic accuracy, using 30-day mortality in patients discharged from the emergency department (ED) as a proxy.
Mortality Aged, 80 and over Retrospective Studies Young Adult Time Factors Electronic Health Records Adult Humans Logistic Models Female Male Machine Learning Emergency Service, Hospital Sweden Middle Aged Registries Aged Patient Discharge
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Development and validation of 15-month mortality prediction models: a retrospective observational comparison of machine-learning techniques in a national sample of Medicare recipients.

BMJ open Jul 16, 2019
OBJECTIVE: The objective is to develop and validate a predictive model for 15-month mortality using a random sample of community-dwelling Medicare beneficiaries.
Bayes Theorem Medicare Mortality Logistic Models Humans United States Neural Networks, Computer Models, Statistical Machine Learning Decision Trees Female Aged Aged, 80 and over Male
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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 Jul 5, 2019
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...
Monitoring, Physiologic Inpatients Mortality Algorithms Prospective Studies Retrospective Studies Electronic Health Records Female Risk Factors Male Middle Aged Risk Assessment Computer Systems Humans Machine Learning
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Can AI Help Reduce Disparities in General Medical and Mental Health Care?

AMA journal of ethics Feb 1, 2019
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 ...
Humans Artificial Intelligence Delivery of Health Care Sex Factors Adult Intensive Care Units Patient Readmission Male Female Mortality Middle Aged Aged Mental Health Services Aged, 80 and over Healthcare Disparities
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Prediction of mortality following pediatric heart transplant using machine learning algorithms.

Pediatric transplantation Jan 29, 2019
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 ...
Registries Heart Failure Pediatrics Calibration Heart Transplantation Multivariate Analysis Mortality Adolescent Child, Preschool Humans Child Neural Networks, Computer Regression Analysis Machine Learning Area Under Curve Algorithms Databases, Factual Female Male Infant
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Development and Validation of Machine Learning Models for Prediction of 1-Year Mortality Utilizing Electronic Medical Record Data Available at the End of Hospitalization in Multicondition Patients: a Proof-of-Concept Study.

Journal of general internal medicine Jan 30, 2018
BACKGROUND: Predicting death in a cohort of clinically diverse, multicondition hospitalized patients is difficult. Prognostic models that use electronic medical record (EMR) data to determine 1-year death risk can improve end-of-life planning and ris...
Risk Factors Hospitalization Humans Aged Machine Learning Aged, 80 and over Data Analysis Adult Forecasting Retrospective Studies Mortality Electronic Health Records Female Reproducibility of Results Male Middle Aged Cohort Studies Models, Theoretical Proof of Concept Study
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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 Dec 19, 2017
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...
Exercise Test Aged Humans Datasets as Topic Machine Learning Cardiorespiratory Fitness Mortality Adult Prognosis Classification Male Female Middle Aged Follow-Up Studies
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