AI Medical Compendium Journal:
American journal of respiratory and critical care medicine

Showing 21 to 29 of 29 articles

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...
Phenotype Interleukin-6 Prognosis Biomarkers, Tumor Humans Machine Learning Bilirubin Pulmonary Ventilation Vital Signs Carbon Dioxide Plasminogen Activator Inhibitor 1 Platelet Count Leukocyte Count Receptors, Tumor Necrosis Factor, Type I Partial Pressure Protein C Serum Albumin Mortality Bicarbonates Blood Pressure Area Under Curve Interleukin-8 Creatinine Vasoconstrictor Agents Oxygen Intercellular Adhesion Molecule-1 Respiratory Distress Syndrome Randomized Controlled Trials as Topic Tidal Volume Latent Class Analysis Inflammation Age Factors
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Assessing the Accuracy of a Deep Learning Method to Risk Stratify Indeterminate Pulmonary Nodules.

American journal of respiratory and critical care medicine Jul 15, 2020
The management of indeterminate pulmonary nodules (IPNs) remains challenging, resulting in invasive procedures and delays in diagnosis and treatment. Strategies to decrease the rate of unnecessary invasive procedures and optimize surveillance regime...
Lung Neoplasms United States Multiple Pulmonary Nodules Algorithms Tomography, X-Ray Computed Deep Learning Radiographic Image Interpretation, Computer-Assisted Humans Neural Networks, Computer
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Childhood Asthma: Advances Using Machine Learning and Mechanistic Studies.

American journal of respiratory and critical care medicine Feb 15, 2019
A paradigm shift brought by the recognition that childhood asthma is an aggregated diagnosis that comprises several different endotypes underpinned by different pathophysiology, coupled with advances in understanding potentially important causal mech...
Big Data Child Immunity, Innate Models, Biological Humans Machine Learning Asthma
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Overfitting and Use of Mismatched Cohorts in Deep Learning Models: Preventable Design Limitations.

American journal of respiratory and critical care medicine Aug 15, 2018
Prognosis Tomography, X-Ray Computed Deep Learning Humans Algorithms Smokers
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Reply to Mummadi et al.: Overfitting and Use of Mismatched Cohorts in Deep Learning Models: Preventable Design Limitations.

American journal of respiratory and critical care medicine Aug 15, 2018
Deep Learning Smokers Thorax Prognosis Tomography, X-Ray Computed Humans
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Artificial Intelligence and Chest Imaging. Will Deep Learning Make Us Smarter?

American journal of respiratory and critical care medicine Jan 15, 2018
Tomography, X-Ray Computed Deep Learning Smokers Artificial Intelligence Prognosis
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Disease Staging and Prognosis in Smokers Using Deep Learning in Chest Computed Tomography.

American journal of respiratory and critical care medicine Jan 15, 2018
RATIONALE: Deep learning is a powerful tool that may allow for improved outcome prediction.
Pulmonary Disease, Chronic Obstructive Male Middle Aged Deep Learning Logistic Models Risk Assessment Severity of Illness Index Female Aged Survival Rate Databases, Factual Prognosis Tomography, X-Ray Computed Humans Respiratory Function Tests Respiratory Distress Syndrome Predictive Value of Tests Smoking
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Finding Asthma: Building a Foundation for Care and Discovery.

American journal of respiratory and critical care medicine Aug 15, 2017
Humans Asthma Natural Language Processing
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Application of a Natural Language Processing Algorithm to Asthma Ascertainment. An Automated Chart Review.

American journal of respiratory and critical care medicine Aug 15, 2017
RATIONALE: Difficulty of asthma ascertainment and its associated methodologic heterogeneity have created significant barriers to asthma care and research.
Child, Preschool Child Female Natural Language Processing Reproducibility of Results Prevalence Humans Risk Factors Adolescent Retrospective Studies Asthma Cohort Studies Electronic Health Records Sensitivity and Specificity Minnesota Male
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