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Age Factors

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Phenotypic clustering of heart failure with preserved ejection fraction reveals different rates of hospitalization.

Journal of cardiovascular medicine (Hagerstown, Md.) Jan 1, 2021
AIMS: Approximately 50% of patients with heart failure have preserved (≥50%) ejection fraction (HFpEF). Improved understanding of the phenotypic heterogeneity of HFpEF might facilitate development of targeted therapies and interventions.
Prevalence Aged Comorbidity Aged, 80 and over Time Factors Natural Language Processing Male United States Heart Failure Ventricular Function, Left Age Factors Data Mining Stroke Volume Cluster Analysis Administrative Claims, Healthcare Humans Middle Aged Databases, Factual Prognosis Retrospective Studies Female Hospitalization
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Deep Learning of Computed Tomography Virtual Wedge Resection for Prediction of Histologic Usual Interstitial Pneumonitis.

Annals of the American Thoracic Society Jan 1, 2021
The computed tomography (CT) pattern of definite or probable usual interstitial pneumonia (UIP) can be diagnostic of idiopathic pulmonary fibrosis and may obviate the need for invasive surgical biopsy. Few machine-learning studies have investigated ...
Idiopathic Pulmonary Fibrosis Lung Diseases, Interstitial Female Aged Humans Male Retrospective Studies Middle Aged Tomography, X-Ray Computed Deep Learning Age Factors
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Determination of disease severity in COVID-19 patients using deep learning in chest X-ray images.

Diagnostic and interventional radiology (Ankara, Turkey) Jan 1, 2021
PURPOSE: Chest X-ray plays a key role in diagnosis and management of COVID-19 patients and imaging features associated with clinical elements may assist with the development or validation of automated image analysis tools. We aimed to identify associ...
Humans COVID-19 Retrospective Studies Female SARS-CoV-2 Deep Learning Age Factors Italy Radiologists Feasibility Studies Radiography, Thoracic Aged Thorax Adult Male Middle Aged Comorbidity Severity of Illness Index
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Machine-learning prediction of unplanned 30-day rehospitalization using the French hospital medico-administrative database.

Medicine Dec 4, 2020
Predicting unplanned rehospitalizations has traditionally employed logistic regression models. Machine learning (ML) methods have been introduced in health service research and may improve the prediction of health outcomes. The objective of this work...
Humans Machine Learning Algorithms Retrospective Studies Health Status Age Factors Emergency Service, Hospital Tertiary Care Centers Sex Factors Patient Readmission France Female Male Comorbidity Severity of Illness Index ROC Curve Socioeconomic Factors
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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...
Receptors, Tumor Necrosis Factor, Type I Partial Pressure Protein C Pulmonary Ventilation Vital Signs Serum Albumin Mortality Bicarbonates Leukocyte Count Randomized Controlled Trials as Topic Tidal Volume Blood Pressure Area Under Curve Interleukin-8 Oxygen Intercellular Adhesion Molecule-1 Creatinine Vasoconstrictor Agents Carbon Dioxide Plasminogen Activator Inhibitor 1 Platelet Count Bilirubin Prognosis Biomarkers, Tumor Latent Class Analysis Inflammation Age Factors Respiratory Distress Syndrome Humans Machine Learning Phenotype Interleukin-6
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Can Machine-learning Algorithms Predict Early Revision TKA in the Danish Knee Arthroplasty Registry?

Clinical orthopaedics and related research Sep 1, 2020
BACKGROUND: Revision TKA is a serious adverse event with substantial consequences for the patient. As the demand for TKA rises, reducing the risk of revision TKA is becoming increasingly important. Predictive tools based on machine-learning algorithm...
Adult Osteoarthritis, Knee Male Humans Middle Aged Denmark Knee Injuries Machine Learning Risk Assessment Predictive Value of Tests Algorithms Postoperative Complications Registries Female Age Factors Body Weight Risk Factors Arthroplasty, Replacement, Knee Aged Reoperation Preoperative Period
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A Novel Machine Learning Model Developed to Assist in Patient Selection for Outpatient Total Shoulder Arthroplasty.

The Journal of the American Academy of Orthopaedic Surgeons Jul 1, 2020
INTRODUCTION: Patient selection for outpatient total shoulder arthroplasty (TSA) is important to optimizing patient outcomes. This study aims to develop a machine learning tool that may aid in patient selection for outpatient total should arthroplast...
Humans Machine Learning Forecasting Decision Support Techniques Female Aged Pulmonary Disease, Chronic Obstructive Male Comorbidity Length of Stay ROC Curve Logistic Models Treatment Outcome Age Factors Arthroplasty, Replacement, Shoulder Patient Selection Sex Factors Outpatients
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Machine Learning and Mechanistic Modeling for Prediction of Metastatic Relapse in Early-Stage Breast Cancer.

JCO clinical cancer informatics Mar 1, 2020
PURPOSE: For patients with early-stage breast cancer, predicting the risk of metastatic relapse is of crucial importance. Existing predictive models rely on agnostic survival analysis statistical tools (eg, Cox regression). Here we define and evaluat...
Tumor Burden Humans Neoplasm Metastasis Machine Learning Algorithms Computer Simulation Female Biomarkers, Tumor Aged Middle Aged Aged, 80 and over Age Factors Young Adult Predictive Value of Tests Adult Neoplasm Staging Survival Rate Neoplasm Recurrence, Local Breast Neoplasms
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Development of a periodontitis risk assessment model for primary care providers in an interdisciplinary setting.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2020
BACKGROUND: Periodontitis (PD), a form of gum disease, is a major public health concern as it is globally prevalent and harms both individual quality of life and economic productivity. Global cost in lost productivity is estimated at US$54 billion an...
Comorbidity Primary Health Care Decision Support Systems, Clinical Logistic Models Socioeconomic Factors Support Vector Machine Aged Aged, 80 and over Young Adult Adult Male Body Weights and Measures Middle Aged Age Factors Oral Hygiene Humans Lipids Neural Networks, Computer Periodontitis Artificial Intelligence Blood Pressure Retrospective Studies Bayes Theorem Female Sex Factors
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A Machine Learning-Based Triage Tool for Children With Acute Infection in a Low Resource Setting.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Dec 1, 2019
OBJECTIVES: To deploy machine learning tools (random forests) to develop a model that reliably predicts hospital mortality in children with acute infections residing in low- and middle-income countries, using age and other variables collected at hosp...
Hospital Mortality Age Factors Infant Humans Infections Triage Machine Learning Severity of Illness Index Vital Signs Developing Countries Prospective Studies Adolescent Child Mortality Prognosis Rwanda Sex Factors Female Child, Preschool Male Child
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