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Lung Diseases, Interstitial

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[Advances in pulmonary pathology in China over the past ten years: retrospect and prospect].

Zhonghua bing li xue za zhi = Chinese journal of pathology
Over the past decade, China has made remarkable achievements in the updating of molecular characteristics and diagnostic criteria of lung cancer, pathological characteristics of COVID-19, classification scheme of interstitial lung disease, applicatio...

Explainable fully automated CT scoring of interstitial lung disease for patients suspected of systemic sclerosis by cascaded regression neural networks and its comparison with experts.

Scientific reports
Visual scoring of interstitial lung disease in systemic sclerosis (SSc-ILD) from CT scans is laborious, subjective and time-consuming. This study aims to develop a deep learning framework to automate SSc-ILD scoring. The automated framework is a casc...

Prognostic value of a composite physiologic index developed by adding bronchial and hyperlucent volumes quantified via artificial intelligence technology.

Respiratory research
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...

Diagnosis of Fibrotic Interstitial Lung Diseases Based on the Combination of Label-Free Quantitative Multiphoton Fiber Histology and Machine Learning.

Laboratory investigation; a journal of technical methods and pathology
Interstitial lung disease (ILD), characterized by inflammation and fibrosis, often suffers from low diagnostic accuracy and consistency. Traditional hematoxylin and eosin (H&E) staining primarily reveals cellular inflammation with limited detail on f...

Automated AI-based image analysis for quantification and prediction of interstitial lung disease in systemic sclerosis patients.

Respiratory research
BACKGROUND: Systemic sclerosis (SSc) is a rare connective tissue disease associated with rapidly evolving interstitial lung disease (ILD), driving its mortality. Specific imaging-based biomarkers associated with the evolution of lung disease are need...

Development and validation of a CT-based radiomics machine learning model for differentiating immune-related interstitial pneumonia.

International immunopharmacology
INTRODUCTION: Immune checkpoint inhibitor-related interstitial pneumonia (CIP) poses a diagnostic challenge due to its radiographic similarity to other pneumonias. We developed a non-invasive model using CT imaging to differentiate CIP from other pne...

A computed tomography-based deep learning radiomics model for predicting the gender-age-physiology stage of patients with connective tissue disease-associated interstitial lung disease.

Computers in biology and medicine
OBJECTIVES: To explore the feasibility of using a diagnostic model constructed with deep learning-radiomics (DLR) features extracted from chest computed tomography (CT) images to predict the gender-age-physiology (GAP) stage of patients with connecti...

Deep Learning for Predicting Acute Exacerbation and Mortality of Interstitial Lung Disease.

Annals of the American Thoracic Society
Some patients with interstitial lung disease (ILD) have a high mortality rate or experience acute exacerbation of ILD (AE-ILD) that results in increased mortality. Early identification of these high-risk patients and accurate prediction of the onset...

Impact of Photon-counting Detector Computed Tomography on a Quantitative Interstitial Lung Disease Machine Learning Model.

Journal of thoracic imaging
PURPOSE: Compare the impact of photon-counting detector computed tomography (PCD-CT) to conventional CT on an interstitial lung disease (ILD) quantitative machine learning (QML) model.