AIMC Topic: Idiopathic Pulmonary Fibrosis
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Machine learning-based integration identifies plasma cells-related gene signature ST6GAL1 in idiopathic pulmonary fibrosis.
BMC pulmonary medicine
Jul 2, 2025
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a rare, progressive, and fibrotic disease with poor prognosis that lacks treatment options. As a major component of the lung adaptive immune system, plasma cells play a crucial regulatory role during...
Diagnosis of early idiopathic pulmonary fibrosis: current status and future perspective.
Respiratory research
May 19, 2025
The standard approach to diagnosing idiopathic pulmonary fibrosis (IPF) includes identifying the usual interstitial pneumonia (UIP) pattern via high resolution computed tomography (HRCT) or lung biopsy and excluding known causes of interstitial lung ...
ITGAV, a specific biomarker associated with the pathogenesis of idiopathic pulmonary fibrosis.
Scientific reports
May 15, 2025
Objective Idiopathic pulmonary fibrosis (IPF), which radiologically/pathologically manifests mainly as usual interstitial pneumonia (UIP), is easily confused with chronic hypersensitivity pneumonitis (CHP) and collagenous vascular disease in clinical...
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...
Integrating machine learning and neural networks for new diagnostic approaches to idiopathic pulmonary fibrosis and immune infiltration research.
PloS one
Apr 24, 2025
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is an interstitial lung disease with a fatal outcome, known for its rapid progression and unpredictable clinical course. However, the tools available for diagnosing and treating IPF are quite limited. T...
Diagnosis accuracy of machine learning for idiopathic pulmonary fibrosis: a systematic review and meta-analysis.
European journal of medical research
Apr 15, 2025
BACKGROUND: The diagnosis of idiopathic pulmonary fibrosis (IPF) is complex, which requires lung biopsy, if necessary, and multidisciplinary discussions with specialists. Clinical diagnosis of the two ailments is particularly challenging due to the i...
Cost-effectiveness of novel diagnostic tools for idiopathic pulmonary fibrosis in the United States.
BMC health services research
Mar 15, 2025
OBJECTIVES: Novel non-invasive machine learning algorithms may improve accuracy and reduce the need for biopsy when diagnosing idiopathic pulmonary fibrosis (IPF). We conducted a cost-effectiveness analysis of diagnostic strategies for IPF.
Common biomarkers of idiopathic pulmonary fibrosis and systemic sclerosis based on WGCNA and machine learning.
Scientific reports
Jan 3, 2025
Interstitial lung disease (ILD) is known to be a major complication of systemic sclerosis (SSc) and a leading cause of death in SSc patients. As the most common type of ILD, the pathogenesis of idiopathic pulmonary fibrosis (IPF) has not been fully e...
Prognostic value of a composite physiologic index developed by adding bronchial and hyperlucent volumes quantified via artificial intelligence technology.
Respiratory research
Dec 24, 2024
BACKGROUND: The composite physiologic index (CPI) was developed to estimate the extent of interstitial lung disease (ILD) in idiopathic pulmonary fibrosis (IPF) patients based on pulmonary function tests (PFTs). The CALIPER-revised version of the CPI...
Integrating machine learning with bioinformatics for predicting idiopathic pulmonary fibrosis prognosis: developing an individualized clinical prediction tool.
Experimental biology and medicine (Maywood, N.J.)
Dec 23, 2024
Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease with a poor prognosis. Its non-specific clinical symptoms make accurate prediction of disease progression challenging. This study aimed to develop molecular-level prognostic m...
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