AIMC Topic: Respiratory Function Tests

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Early heart rate variability evaluation enables to predict ICU patients' outcome.

Scientific reports Feb 15, 2022
Heart rate variability (HRV) is a mean to evaluate cardiac effects of autonomic nervous system activity, and a relation between HRV and outcome has been proposed in various types of patients. We attempted to evaluate the best determinants of such var...
Female Aged Male Middle Aged Machine Learning Prospective Studies Prognosis Intensive Care Units Electrocardiography Oxygen Saturation Heart Rate Respiratory Function Tests Patient Admission Respiration, Artificial Severity of Illness Index Length of Stay Humans Hospital Mortality Neural Networks, Computer
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Artificial intelligence for quality control of oscillometry measures.

Computers in biology and medicine Sep 14, 2021
BACKGROUND: The forced oscillation technique (FOT) allows non-invasive lung function testing during quiet breathing even without expert guidance. However, it still relies on an operator for excluding breaths with artefacts such as swallowing, glottis...
Humans Artificial Intelligence Quality Control Respiratory Function Tests Artifacts Oscillometry
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Deep radiomics-based survival prediction in patients with chronic obstructive pulmonary disease.

Scientific reports Jul 26, 2021
Heterogeneous clinical manifestations and progression of chronic obstructive pulmonary disease (COPD) affect patient health risk assessment, stratification, and management. Pulmonary function tests are used to diagnose and classify the severity of CO...
Tomography, X-Ray Computed Republic of Korea Female Aged Pulmonary Disease, Chronic Obstructive Humans Neural Networks, Computer Malaysia Male Predictive Value of Tests Survival Analysis Middle Aged Respiratory Function Tests Deep Learning Cohort Studies
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A Machine Learning Approach to the Interpretation of Cardiopulmonary Exercise Tests: Development and Validation.

Pulmonary medicine May 31, 2021
OBJECTIVE: At present, there is no consensus on the best strategy for interpreting the cardiopulmonary exercise test's (CPET) results. This study is aimed at assessing the potential of using computer-aided algorithms to evaluate CPET data for identif...
Middle Aged Aged Support Vector Machine Adult Chronic Disease Pulmonary Disease, Chronic Obstructive Predictive Value of Tests Humans Male Exercise Test Machine Learning Heart Failure Retrospective Studies Respiratory Function Tests Female
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Improved detection of air trapping on expiratory computed tomography using deep learning.

PloS one Mar 24, 2021
BACKGROUND: Radiologic evidence of air trapping (AT) on expiratory computed tomography (CT) scans is associated with early pulmonary dysfunction in patients with cystic fibrosis (CF). However, standard techniques for quantitative assessment of AT are...
Deep Learning Child Regression Analysis Respiratory Function Tests Neural Networks, Computer Tomography, X-Ray Computed Female Male Air Exhalation Humans
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Deep neural network analyses of spirometry for structural phenotyping of chronic obstructive pulmonary disease.

JCI insight Jul 9, 2020
BACKGROUNDCurrently recommended traditional spirometry outputs do not reflect the relative contributions of emphysema and airway disease to airflow obstruction. We hypothesized that machine-learning algorithms can be trained on spirometry data to ide...
Adult Pulmonary Disease, Chronic Obstructive Male Middle Aged Smoking Respiratory Function Tests Spirometry Lung Pulmonary Emphysema Humans Neural Networks, Computer Female Aged
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Machine Learning and Prediction of All-Cause Mortality in COPD.

Chest Apr 27, 2020
BACKGROUND: COPD is a leading cause of mortality.
Humans Machine Learning Female Pulmonary Disease, Chronic Obstructive Male Middle Aged Predictive Value of Tests Cause of Death Respiratory Function Tests
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Comparison of Artificial Intelligence-Based Fully Automatic Chest CT Emphysema Quantification to Pulmonary Function Testing.

AJR. American journal of roentgenology Mar 4, 2020
The purpose of this study was to evaluate an artificial intelligence (AI)-based prototype algorithm for fully automated quantification of emphysema on chest CT compared with pulmonary function testing (spirometry). A total of 141 patients (72 women...
Radiographic Image Interpretation, Computer-Assisted Pulmonary Emphysema Respiratory Function Tests Aged, 80 and over Adult Male Middle Aged Retrospective Studies Tomography, X-Ray Computed Female Aged Humans Artificial Intelligence
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Machine Learning Characterization of COPD Subtypes: Insights From the COPDGene Study.

Chest Dec 28, 2019
COPD is a heterogeneous syndrome. Many COPD subtypes have been proposed, but there is not yet consensus on how many COPD subtypes there are and how they should be defined. The COPD Genetic Epidemiology Study (COPDGene), which has generated 10-year lo...
Machine Learning Phenotype Pulmonary Disease, Chronic Obstructive Disease Progression Humans Respiratory Function Tests Molecular Epidemiology Genome-Wide Association Study Genetic Predisposition to Disease Cluster Analysis Diagnostic Imaging
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Diagnostic value of spirometry vs impulse oscillometry: A comparative study in children with sickle cell disease.

Pediatric pulmonology Jun 18, 2019
BACKGROUND: Spirometry is conventionally used to diagnose airway diseases in children with sickle cell disease (C-SCD). However, spirometry is difficult for younger children to perform, is effort dependent, and it provides limited information on resp...
Vital Capacity Bronchodilator Agents Oscillometry Adolescent Child, Preschool Child ROC Curve Anemia, Sickle Cell Respiratory Function Tests Spirometry Respiratory Mechanics Asthma Male Lung Case-Control Studies Humans Machine Learning Retrospective Studies Female
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