AIMC Topic: Idiopathic Pulmonary Fibrosis

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Artificial intelligence identifies inflammation and confirms fibroblast foci as prognostic tissue biomarkers in idiopathic pulmonary fibrosis.

Human pathology
A large number of fibroblast foci (FF) predict mortality in idiopathic pulmonary fibrosis (IPF). Other prognostic histological markers have not been identified. Artificial intelligence (AI) offers a possibility to quantitate possible prognostic histo...

Deep learning in interstitial lung disease-how long until daily practice.

European radiology
Interstitial lung diseases are a diverse group of disorders that involve inflammation and fibrosis of interstitium, with clinical, radiological, and pathological overlapping features. These are an important cause of morbidity and mortality among lung...

Use of a molecular classifier to identify usual interstitial pneumonia in conventional transbronchial lung biopsy samples: a prospective validation study.

The Lancet. Respiratory medicine
BACKGROUND: In the appropriate clinical setting, the diagnosis of idiopathic pulmonary fibrosis (IPF) requires a pattern of usual interstitial pneumonia to be present on high-resolution chest CT (HRCT) or surgical lung biopsy. A molecular usual inter...

Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study.

The Lancet. Respiratory medicine
BACKGROUND: Based on international diagnostic guidelines, high-resolution CT plays a central part in the diagnosis of fibrotic lung disease. In the correct clinical context, when high-resolution CT appearances are those of usual interstitial pneumoni...

Serum Levels of Visfatin, Omentin and Irisin in Patients with End-Stage Lung Disease Before and After Lung Transplantation.

Annals of transplantation
BACKGROUND The aim of this study was to investigate serum concentrations of visfatin, irisin, and omentin in patients with end-stage lung diseases (ESLD) before and after lung transplantation (LTx) and to find relationship between adipokines levels a...

MetaKTSP: a meta-analytic top scoring pair method for robust cross-study validation of omics prediction analysis.

Bioinformatics (Oxford, England)
MOTIVATION: Supervised machine learning is widely applied to transcriptomic data to predict disease diagnosis, prognosis or survival. Robust and interpretable classifiers with high accuracy are usually favored for their clinical and translational pot...

Efficacy and safety of inhaled N-acetylcysteine in idiopathic pulmonary fibrosis: A prospective, single-arm study.

Respiratory investigation
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with few treatment options. The efficacy of N-acetylcysteine in patients with IPF remains controversial. The aim of this research was to investigate the efficacy of inhaled...

Current State of Fibrotic Interstitial Lung Disease Imaging.

Radiology
Interstitial lung disease (ILD) diagnosis is complex, continuously evolving, and increasingly reliant on thin-section chest CT. Multidisciplinary discussion aided by a thorough radiologic review can achieve a high-confidence diagnosis of ILD in the m...

Identification of genetic indicators linked to immunological infiltration in idiopathic pulmonary fibrosis.

Medicine
This study employed bioinformatics to investigate potential molecular markers associated with idiopathic pulmonary fibrosis (IPF) and examined their correlation with immune-infiltrating cells. Microarray data for IPF were retrieved from the Gene Expr...

From pixels to prognosis: unlocking the potential of deep learning in fibrotic lung disease imaging analysis.

The British journal of radiology
The licensing of antifibrotic therapy for fibrotic lung diseases, including idiopathic pulmonary fibrosis (IPF), has created an urgent need for reliable biomarkers to predict disease progression and treatment response. Some patients experience stable...