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Vital Capacity

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Deep learning for spirometry quality assurance with spirometric indices and curves.

Respiratory research
BACKGROUND: Spirometry quality assurance is a challenging task across levels of healthcare tiers, especially in primary care. Deep learning may serve as a support tool for enhancing spirometry quality. We aimed to develop a high accuracy and sensitiv...

Deep Learning-based Approach to Predict Pulmonary Function at Chest CT.

Radiology
Background Low-dose chest CT screening is recommended for smokers with the potential for lung function abnormality, but its role in predicting lung function remains unclear. Purpose To develop a deep learning algorithm to predict pulmonary function w...

Deep learning-based prognostication in idiopathic pulmonary fibrosis using chest radiographs.

European radiology
OBJECTIVES: To develop and validate a deep learning-based prognostic model in patients with idiopathic pulmonary fibrosis (IPF) using chest radiographs.

Value of CT quantification in progressive fibrosing interstitial lung disease: a deep learning approach.

European radiology
OBJECTIVES: To evaluate the relationship of changes in the deep learning-based CT quantification of interstitial lung disease (ILD) with changes in forced vital capacity (FVC) and visual assessments of ILD progression, and to investigate their progno...

Curve-Modelling and Machine Learning for a Better COPD Diagnosis.

International journal of chronic obstructive pulmonary disease
BACKGROUND: Development of new tools in artificial intelligence has an outstanding performance in the recognition of multidimensional patterns, which is why they have proven to be useful in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD...

Machine learning classifier is associated with mortality in interstitial lung disease: a retrospective validation study leveraging registry data.

BMC pulmonary medicine
BACKGROUND: Mortality prediction in interstitial lung disease (ILD) poses a significant challenge to clinicians due to heterogeneity across disease subtypes. Currently, forced vital capacity (FVC) and Gender, Age, and Physiology (GAP) score are the t...

A deep learning-based model to estimate pulmonary function from chest x-rays: multi-institutional model development and validation study in Japan.

The Lancet. Digital health
BACKGROUND: Chest x-ray is a basic, cost-effective, and widely available imaging method that is used for static assessments of organic diseases and anatomical abnormalities, but its ability to estimate dynamic measurements such as pulmonary function ...

Association of Deep Learning-based Chest CT-derived Respiratory Parameters with Disease Progression in Amyotrophic Lateral Sclerosis.

Radiology
Background Forced vital capacity (FVC) is a standard measure of respiratory function in patients with amyotrophic lateral sclerosis (ALS) but has limitations, particularly for patients with bulbar impairment. Purpose To determine the value of deep le...