AIMC Topic: Mortality

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Machine Learning Can Unlock Insights Into Mortality.

American journal of public health Jul 1, 2021
Public Health Surveillance Medical Records Mortality Decision Making, Computer-Assisted Insurance Claim Review Humans Machine Learning Algorithms United States
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COVID-19 mortality rate prediction for India using statistical neural networks and gaussian process regression model.

African health sciences Mar 1, 2021
The primary purpose of this research is to identify the best COVID-19 mortality model for India using regression models and is to estimate the future COVID-19 mortality rate for India. Specifically, Statistical Neural Networks (Radial Basis Function ...
SARS-CoV-2 India Models, Statistical Regression Analysis Models, Biological Humans Neural Networks, Computer Pandemics COVID-19 Forecasting Mortality
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Using machine learning to estimate the effect of racial segregation on COVID-19 mortality in the United States.

Proceedings of the National Academy of Sciences of the United States of America Feb 16, 2021
This study examines the role that racial residential segregation has played in shaping the spread of COVID-19 in the United States as of September 30, 2020. The analysis focuses on the effects of racial residential segregation on mortality and infect...
Mortality Social Segregation Risk Factors United States Socioeconomic Factors Regression Analysis Ethnicity Humans Machine Learning COVID-19 SARS-CoV-2
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Low Predictability of Readmissions and Death Using Machine Learning in Cirrhosis.

The American journal of gastroenterology Feb 1, 2021
INTRODUCTION: Readmission and death in cirrhosis are common, expensive, and difficult to predict. Our aim was to evaluate the abilities of multiple artificial intelligence (AI) techniques to predict clinical outcomes based on variables collected at a...
Humans Machine Learning Anti-Bacterial Agents Severity of Illness Index Cohort Studies ROC Curve Logistic Models Liver Cirrhosis Female Reproducibility of Results Aged Male Middle Aged Infections Hepatic Encephalopathy Paracentesis Mortality Lactulose beta-Lactams Adrenergic beta-Antagonists Clinical Decision Rules End Stage Liver Disease Rifaximin Gastrointestinal Agents Water-Electrolyte Imbalance Patient Readmission Gastrointestinal Hemorrhage Proton Pump Inhibitors Support Vector Machine Kidney Diseases Hydrothorax Ascites
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Machine learning-based prediction of adverse events following an acute coronary syndrome (PRAISE): a modelling study of pooled datasets.

Lancet (London, England) Jan 16, 2021
BACKGROUND: The accuracy of current prediction tools for ischaemic and bleeding events after an acute coronary syndrome (ACS) remains insufficient for individualised patient management strategies. We developed a machine learning-based risk stratifica...
Male Postoperative Complications Hemorrhage Acute Coronary Syndrome Datasets as Topic Mortality Humans Machine Learning Clinical Decision-Making Female 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 Oct 1, 2020
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...
Leukocyte Count Receptors, Tumor Necrosis Factor, Type I Partial Pressure Protein C Humans Machine Learning Phenotype Interleukin-6 Prognosis Biomarkers, Tumor Latent Class Analysis Inflammation Vasoconstrictor Agents Carbon Dioxide Plasminogen Activator Inhibitor 1 Platelet Count Bilirubin Pulmonary Ventilation Vital Signs Serum Albumin Mortality Bicarbonates Area Under Curve Interleukin-8 Oxygen Intercellular Adhesion Molecule-1 Creatinine Age Factors Respiratory Distress Syndrome Randomized Controlled Trials as Topic Tidal Volume Blood Pressure
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From development to deployment: dataset shift, causality, and shift-stable models in health AI.

Biostatistics (Oxford, England) Apr 1, 2020
Mortality Biostatistics Artificial Intelligence Biomedical Research Models, Theoretical Causality Datasets as Topic Humans
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Quantifying risk factors in medical reports with a context-aware linear model.

Journal of the American Medical Informatics Association : JAMIA Jun 1, 2019
OBJECTIVE: We seek to quantify the mortality risk associated with mentions of medical concepts in textual electronic health records (EHRs). Recognizing mentions of named entities of relevant types (eg, conditions, symptoms, laboratory tests or behavi...
Natural Language Processing Linear Models Mortality Humans Machine Learning Electronic Health Records Risk Factors Risk Assessment
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Does Robotic Beating Heart Connector Totally Endoscopic Coronary Artery Bypass Bridge the Gender Gap in Coronary Bypass Surgery?

Innovations (Philadelphia, Pa.) Jan 1, 2018
OBJECTIVE: Previous studies have shown that women carry a higher risk of morbidity and mortality after coronary artery bypass surgery. We investigated gender differences in risk factors and outcomes in our patients undergoing robotic beating heart co...
Length of Stay Treatment Outcome Robotics Coronary Artery Bypass, Off-Pump Morbidity Risk Factors Aged Endoscopy Male Middle Aged Coronary Artery Bypass Mortality Mammary Arteries Gender Identity Peripheral Vascular Diseases Humans Retrospective Studies Female
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Selection and Short-Term Outcomes of Living Kidney Donors in Singapore - An Analysis of the Donor Care Registry.

Annals of the Academy of Medicine, Singapore Nov 1, 2017
INTRODUCTION: Transplant rates in Singapore have been falling and there is limited information on baseline characteristics and clinical outcomes of living kidney donors nationally. This study aimed to determine the safety of living kidney donor trans...
Singapore Registries Proportional Hazards Models Multivariate Analysis Nephrectomy Mortality Lost to Follow-Up Glomerular Filtration Rate Follow-Up Studies Age Factors Living Donors Kidney Failure, Chronic Humans Kidney Transplantation Postoperative Complications Renal Insufficiency, Chronic
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