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Mortality

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Representation learning for clinical time series prediction tasks in electronic health records.

BMC medical informatics and decision making 31842854
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 China Comorbidity Electronic Health Records Forecasting Heart Failure Humans Machine Learning Mortality Neural Networks, Computer
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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 32023993
(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 ...
Alcoholic Intoxication Area Under Curve Logistic Models Machine Learning Mortality Neural Networks, Computer Republic of Korea Risk Assessment
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Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy.

Critical care (London, England) 32028984
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...
Acute Kidney Injury Aged Aged, 80 and over Algorithms APACHE Area Under Curve Continuous Renal Replacement Therapy Female Humans Machine Learning Male Middle Aged Mortality Organ Dysfunction Scores Republic of Korea Risk Factors ROC Curve Severity of Illness Index
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Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network.

Nature medicine 32393799
The electrocardiogram (ECG) is a widely used medical test, consisting of voltage versus time traces collected from surface recordings over the heart. Here we hypothesized that a deep neural network (DNN) can predict an important future clinical event...
Adult Aged Aged, 80 and over Algorithms Area Under Curve Cardiologists Cause of Death Deep Learning Electrocardiography Female Humans Male Middle Aged Mortality Neural Networks, Computer Prognosis Proportional Hazards Models Retrospective Studies Risk Assessment ROC Curve
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From development to deployment: dataset shift, causality, and shift-stable models in health AI.

Biostatistics (Oxford, England) 31742354
Artificial Intelligence Biomedical Research Biostatistics Causality Datasets as Topic Humans Models, Theoretical Mortality
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Update to 'Deep-learning model for predicting 30-day postoperative mortality' (Br J Anaesth 2019; 123: 688-95).

British journal of anaesthesia 32389391
Deep Learning Forecasting Humans Mortality Postoperative Period
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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 32366838
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...
Adult Aged Female Humans Machine Learning Male Middle Aged Models, Biological Mortality Peritoneal Dialysis Predictive Value of Tests Prospective Studies Republic of Korea Risk Factors
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A machine learning approach for mortality prediction only using non-invasive parameters.

Medical & biological engineering & computing 32691219
At present, the traditional scoring methods generally utilize laboratory measurements to predict mortality. It results in difficulties of early mortality prediction in the rural areas lack of professional laboratorians and medical laboratory equipmen...
Algorithms Area Under Curve Critical Care Female Hospital Mortality Humans Machine Learning Male Mortality Reproducibility of Results
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Development, implementation, and prospective validation of a model to predict 60-day end-of-life in hospitalized adults upon admission at three sites.

BMC medical informatics and decision making 32894128
BACKGROUND: Automated systems that use machine learning to estimate a patient's risk of death are being developed to influence care. There remains sparse transparent reporting of model generalizability in different subpopulations especially for imple...
Adolescent Adult Aged Aged, 80 and over Electronic Health Records Female Hospitalization Humans Machine Learning Male Middle Aged Mortality Patient Admission Prognosis Prospective Studies Young Adult
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Machine Learning Classifier Models Can Identify Acute Respiratory Distress Syndrome Phenotypes Using Readily Available Clinical Data.

American journal of respiratory and critical care medicine 32551817
Two distinct phenotypes of acute respiratory distress syndrome (ARDS) with differential clinical outcomes and responses to randomly assigned treatment have consistently been identified in randomized controlled trial cohorts using latent class analys...
Age Factors Area Under Curve Bicarbonates Bilirubin Biomarkers, Tumor Blood Pressure Carbon Dioxide Creatinine Humans Inflammation Intercellular Adhesion Molecule-1 Interleukin-6 Interleukin-8 Latent Class Analysis Leukocyte Count Machine Learning Mortality Oxygen Partial Pressure Phenotype Plasminogen Activator Inhibitor 1 Platelet Count Prognosis Protein C Pulmonary Ventilation Randomized Controlled Trials as Topic Receptors, Tumor Necrosis Factor, Type I Respiratory Distress Syndrome Serum Albumin Tidal Volume Vasoconstrictor Agents Vital Signs
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