AIMC Topic: Pulmonary Fibrosis
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Integrating CT radiomics and clinical features using machine learning to predict post-COVID pulmonary fibrosis.
Respiratory research
Jul 2, 2025
BACKGROUND: The lack of reliable biomarkers for the early detection and risk stratification of post-COVID-19 pulmonary fibrosis (PCPF) underscores the urgency advanced predictive tools. This study aimed to develop a machine learning-based predictive ...
Current State of Fibrotic Interstitial Lung Disease Imaging.
Radiology
Jul 1, 2025
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...
Machine learning-driven imaging data for early prediction of lung toxicity in breast cancer radiotherapy.
Scientific reports
May 27, 2025
One possible adverse effect of breast irradiation is the development of pulmonary fibrosis. The aim of this study was to determine whether planning CT scans can predict which patients are more likely to develop lung lesions after treatment. A retrosp...
From pixels to prognosis: unlocking the potential of deep learning in fibrotic lung disease imaging analysis.
The British journal of radiology
Sep 1, 2024
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...
Deep Learning Assessment of Progression of Emphysema and Fibrotic Interstitial Lung Abnormality.
American journal of respiratory and critical care medicine
Sep 15, 2023
Although studies have evaluated emphysema and fibrotic interstitial lung abnormality individually, less is known about their combined progression. To define clinically meaningful progression of fibrotic interstitial lung abnormality in smokers with...
Computer-Aided Diagnosis of Pulmonary Fibrosis Using Deep Learning and CT Images.
Investigative radiology
Oct 1, 2019
OBJECTIVES: The objective of this study is to assess the performance of a computer-aided diagnosis (CAD) system (INTACT system) for the automatic classification of high-resolution computed tomography images into 4 radiological diagnostic categories a...
Serum Amyloid P-component Level May be a Biomarker for Lung Toxicities and Overall Survival after Thoracic Radiotherapy for Non-small Cell Lung Cancer.
Clinical laboratory
Nov 1, 2016
BACKGROUND: Serum amyloid P-component (SAP) contributes to the clearance of apoptotic cells. As one of the main acute-phase reactants, SAP regulates key aspects of inflammation and sets a threshold for immune cell activation. This study aimed to inve...
Kaplan-Meier Estimate
Radiation Pneumonitis
Serum Amyloid P-Component
Proportional Hazards Models
Enzyme-Linked Immunosorbent Assay
Carcinoma, Non-Small-Cell Lung
Biomarkers, Tumor
Multivariate Analysis
Humans
Treatment Outcome
Predictive Value of Tests
Time Factors
Risk Factors
Pulmonary Fibrosis
Lung Neoplasms
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