AIMC Topic: Spirometry

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Chronic obstructive lung disease "expert system": validation of a predictive tool for assisting diagnosis.

International journal of chronic obstructive pulmonary disease
PURPOSE: The purposes of this study were development and validation of an expert system (ES) aimed at supporting the diagnosis of chronic obstructive lung disease (COLD).

Persistent light to moderate alcohol intake and lung function: A longitudinal study.

Alcohol (Fayetteville, N.Y.)
Alcohol intake has been inconsistently associated with lung function levels in cross-sectional studies. The goal of our study was to determine whether longitudinally assessed light-to-moderate alcohol intake is associated with levels and decline of l...

Automated Spirometry Quality Assurance: Supervised Learning From Multiple Experts.

IEEE journal of biomedical and health informatics
Forced spirometry testing is gradually becoming available across different healthcare tiers including primary care. It has been demonstrated in earlier work that commercially available spirometers are not fully able to assure the quality of individua...

Neuro-fuzzy classification of asthma and chronic obstructive pulmonary disease.

BMC medical informatics and decision making
BACKGROUND: This paper presents a system for classification of asthma and chronic obstructive pulmonary disease (COPD) based on fuzzy rules and the trained neural network.

A Comparison of SVM and GMM-Based Classifier Configurations for Diagnostic Classification of Pulmonary Sounds.

IEEE transactions on bio-medical engineering
GOAL: The aim of this study is to find a useful methodology to classify multiple distinct pulmonary conditions including the healthy condition and various pathological types, using pulmonary sounds data.

Deep Learning-Based Chronic Obstructive Pulmonary Disease Exacerbation Prediction Using Flow-Volume and Volume-Time Curve Imaging: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a common and progressive respiratory condition characterized by persistent airflow limitation and symptoms such as dyspnea, cough, and sputum production. Acute exacerbations (AE) of COPD (AE...

Evaluating the Cumulative Benefit of Inspiratory CT, Expiratory CT, and Clinical Data for COPD Diagnosis and Staging through Deep Learning.

Radiology. Cardiothoracic imaging
Purpose To measure the benefit of single-phase CT, inspiratory-expiratory CT, and clinical data for convolutional neural network (CNN)-based chronic obstructive pulmonary disease (COPD) staging. Materials and Methods This retrospective study included...

Deep learning using multilayer perception improves the diagnostic acumen of spirometry: a single-centre Canadian study.

BMJ open respiratory research
RATIONALE: Spirometry and plethysmography are the gold standard pulmonary function tests (PFT) for diagnosis and management of lung disease. Due to the inaccessibility of plethysmography, spirometry is often used alone but this leads to missed or mis...

Area under the expiratory flow-volume curve: predicted values by regression and deep learning methods and recommendations for clinical practice.

BMJ open respiratory research
BACKGROUND: In spirometry, the area under expiratory flow-volume curve (AEX-FV) was found to perform well in diagnosing and stratifying physiologic impairments, potentially lessening the need for complex lung volume testing. Expanding on prior work, ...

Improving Detection of Early Chronic Obstructive Pulmonary Disease.

Annals of the American Thoracic Society
Despite being a major cause of morbidity and mortality, chronic obstructive pulmonary disease (COPD) is frequently undiagnosed. Yet the burden of disease among the undiagnosed is significant, as these individuals experience symptoms, exacerbations, a...