AIMC Topic: Mortality

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Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea.

Scientific reports May 4, 2020
Herein, we aim to assess mortality risk prediction in peritoneal dialysis patients using machine-learning algorithms for proper prognosis prediction. A total of 1,730 peritoneal dialysis patients in the CRC for ESRD prospective cohort from 2008 to 20...
Humans Machine Learning Prospective Studies Middle Aged Republic of Korea Predictive Value of Tests Models, Biological Mortality Peritoneal Dialysis Female Risk Factors Aged Adult Male
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Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy.

Critical care (London, England) Feb 6, 2020
BACKGROUND: Previous scoring models such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) and the Sequential Organ Failure Assessment (SOFA) scoring systems do not adequately predict mortality of patients undergoing co...
Mortality ROC Curve Area Under Curve APACHE Organ Dysfunction Scores Continuous Renal Replacement Therapy Acute Kidney Injury Republic of Korea Female Risk Factors Aged Humans Aged, 80 and over Machine Learning Male Algorithms Middle Aged Severity of Illness Index
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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 ...
Neural Networks, Computer Machine Learning Mortality Alcoholic Intoxication Republic of Korea Risk Assessment Logistic Models Area Under Curve
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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...
Humans Neural Networks, Computer China Heart Failure Mortality Machine Learning Algorithms Forecasting Electronic Health Records Comorbidity
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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...
Area Under Curve Pediatrics Mortality Cohort Studies Child, Preschool Retrospective Studies Child Critical Illness Humans ROC Curve Republic of Korea Female Risk Assessment Male Infant Deep Learning Big Data Adolescent
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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.
Registries Patient Discharge Mortality Middle Aged Time Factors Logistic Models Emergency Service, Hospital Retrospective Studies Electronic Health Records Female Sweden Aged Aged, 80 and over Young Adult Adult Male Humans Machine Learning
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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 Humans Neural Networks, Computer Medicare Mortality Male Logistic Models United States Machine Learning Models, Statistical Female Decision Trees Aged Aged, 80 and over
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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...
Humans Machine Learning Algorithms Prospective Studies Retrospective Studies Electronic Health Records Female Computer Systems Risk Factors Monitoring, Physiologic Male Inpatients Middle Aged Mortality Risk Assessment
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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 ...
Delivery of Health Care Intensive Care Units Sex Factors Adult Humans Female Male Patient Readmission Artificial Intelligence Aged Middle Aged Mortality 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 ...
Child, Preschool Multivariate Analysis Child Mortality Regression Analysis Registries Humans Databases, Factual Heart Failure Neural Networks, Computer Area Under Curve Pediatrics Female Machine Learning Calibration Male Heart Transplantation Algorithms Infant Adolescent
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