AIMC Topic: Vital Capacity

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Minimum clinically important difference in Quantitative Lung Fibrosis score associated with all-cause mortality in idiopathic pulmonary fibrosis: subanalysis from two phase II trials of pamrevlumab.

BMJ open May 12, 2025
OBJECTIVES: Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease. Chest high-resolution CT (HRCT) is instrumental in IPF management, and the Quantitative Lung Fibrosis (QLF) score is a computer-assisted metric for quantifyin...
Vital Capacity Humans Minimal Clinically Important Difference Lung Prospective Studies Tomography, X-Ray Computed Antibodies, Monoclonal, Humanized Female Idiopathic Pulmonary Fibrosis Antibodies, Monoclonal Aged Male Middle Aged Disease Progression
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Machine-Learning-Based Computed Tomography Radiomics Regression Model for Predicting Pulmonary Function.

Academic radiology Apr 10, 2025
RATIONALE AND OBJECTIVES: Chest computed tomography (CT) radiomics can be utilized for categorical predictions; however, models predicting pulmonary function indices directly are lacking. This study aimed to develop machine-learning-based regression ...
Female Aged Adult Radiomics Humans Machine Learning Retrospective Studies Tomography, X-Ray Computed Forced Expiratory Volume Radiographic Image Interpretation, Computer-Assisted Respiratory Function Tests Vital Capacity Male Middle Aged Lung Regression Analysis
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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 Jul 8, 2024
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 ...
Lung Deep Learning Forced Expiratory Volume Japan Radiography, Thoracic Aged Respiratory Function Tests Adult Spirometry Male Vital Capacity Middle Aged Humans Retrospective Studies Female
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Curve-Modelling and Machine Learning for a Better COPD Diagnosis.

International journal of chronic obstructive pulmonary disease Jun 12, 2024
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...
Bronchodilator Agents Peak Expiratory Flow Rate Pulmonary Disease, Chronic Obstructive Male Middle Aged Lung Diagnosis, Computer-Assisted Predictive Value of Tests Spirometry Vital Capacity Machine Learning Female Reproducibility of Results Aged Humans Neural Networks, Computer
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Machine learning classifier is associated with mortality in interstitial lung disease: a retrospective validation study leveraging registry data.

BMC pulmonary medicine May 23, 2024
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...
Prognosis Retrospective Studies Tomography, X-Ray Computed Female Humans Machine Learning Idiopathic Pulmonary Fibrosis Registries Lung Diseases, Interstitial Proportional Hazards Models Aged Male Middle Aged Follow-Up Studies Vital Capacity
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Deep learning-based prognostication in idiopathic pulmonary fibrosis using chest radiographs.

European radiology Dec 19, 2023
OBJECTIVES: To develop and validate a deep learning-based prognostic model in patients with idiopathic pulmonary fibrosis (IPF) using chest radiographs.
Humans Prognosis Retrospective Studies Female Aged Radiography, Thoracic Male Vital Capacity Middle Aged Deep Learning Idiopathic Pulmonary Fibrosis
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Value of CT quantification in progressive fibrosing interstitial lung disease: a deep learning approach.

European radiology Dec 12, 2023
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...
Lung Diseases, Interstitial Vital Capacity Retrospective Studies Tomography, X-Ray Computed Female Aged Male Middle Aged Humans Disease Progression Prognosis Deep Learning
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Prognostic value of deep learning-based fibrosis quantification on chest CT in idiopathic pulmonary fibrosis.

European radiology Mar 16, 2023
OBJECTIVE: To investigate the prognostic value of deep learning (DL)-driven CT fibrosis quantification in idiopathic pulmonary fibrosis (IPF).
Fibrosis Carbon Monoxide Vital Capacity Male Lung Deep Learning Idiopathic Pulmonary Fibrosis Prognosis Retrospective Studies Tomography, X-Ray Computed Humans Aged
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Deep Learning-based Approach to Predict Pulmonary Function at Chest CT.

Radiology Feb 14, 2023
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...
Humans Retrospective Studies Tomography, X-Ray Computed Forced Expiratory Volume Spirometry Male Vital Capacity Middle Aged Lung Deep Learning
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Deep learning for spirometry quality assurance with spirometric indices and curves.

Respiratory research Apr 21, 2022
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...
Vital Capacity Humans Forced Expiratory Volume Deep Learning Quality Control Respiratory Function Tests Spirometry
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