AIMC Topic: Idiopathic Pulmonary Fibrosis
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Deep-learning algorithm to detect fibrosing interstitial lung disease on chest radiographs.
The European respiratory journal
Feb 16, 2023
BACKGROUND: Antifibrotic therapies are available to treat chronic fibrosing interstitial lung diseases (CF-ILDs), including idiopathic pulmonary fibrosis. Early use of these treatments is recommended to slow deterioration of respiratory function and ...
Multi-scale, domain knowledge-guided attention + random forest: a two-stage deep learning-based multi-scale guided attention models to diagnose idiopathic pulmonary fibrosis from computed tomography images.
Medical physics
Nov 5, 2022
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, irreversible, and usually fatal lung disease of unknown reasons, generally affecting the elderly population. Early diagnosis of IPF is crucial for triaging patients' treatment planning...
Deep Learning for Estimating Lung Capacity on Chest Radiographs Predicts Survival in Idiopathic Pulmonary Fibrosis.
Radiology
Oct 25, 2022
Background Total lung capacity (TLC) has been estimated with use of chest radiographs based on time-consuming methods, such as planimetric techniques and manual measurements. Purpose To develop a deep learning-based, multidimensional model capable of...
Unsupervised machine learning identifies predictive progression markers of IPF.
European radiology
Sep 6, 2022
OBJECTIVES: To identify and evaluate predictive lung imaging markers and their pathways of change during progression of idiopathic pulmonary fibrosis (IPF) from sequential data of an IPF cohort. To test if these imaging markers predict outcome.
Predicting Usual Interstitial Pneumonia Histopathology From Chest CT Imaging With Deep Learning.
Chest
Apr 8, 2022
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, often fatal form of interstitial lung disease (ILD) characterized by the absence of a known cause and usual interstitial pneumonitis (UIP) pattern on chest CT imaging and/or histopatho...
MIXTURE of human expertise and deep learning-developing an explainable model for predicting pathological diagnosis and survival in patients with interstitial lung disease.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Feb 23, 2022
Interstitial pneumonia is a heterogeneous disease with a progressive course and poor prognosis, at times even worse than those in the main cancer types. Histopathological examination is crucial for its diagnosis and estimation of prognosis. However, ...
: An Automated Diagnosis of Pulmonary Fibrosis Progression Prediction Using Honeycombing and Deep Learning.
Computational intelligence and neuroscience
Jan 28, 2022
Pulmonary fibrosis is a severe chronic lung disease that causes irreversible scarring in the tissues of the lungs, which results in the loss of lung capacity. The Forced Vital Capacity () of the patient is an interesting measure to investigate this d...
Wet-dry-wet drug screen leads to the synthesis of TS1, a novel compound reversing lung fibrosis through inhibition of myofibroblast differentiation.
Cell death & disease
Dec 17, 2021
Therapies halting the progression of fibrosis are ineffective and limited. Activated myofibroblasts are emerging as important targets in the progression of fibrotic diseases. Previously, we performed a high-throughput screen on lung fibroblasts and s...
Prospective machine learning CT quantitative evaluation of idiopathic pulmonary fibrosis in patients undergoing anti-fibrotic treatment using low- and ultra-low-dose CT.
Clinical radiology
Dec 7, 2021
AIM: To compare the machine learning computed tomography (CT) quantification tool, Computer-Aided Lung Informatics for Pathology Evaluation and Ratings (CALIPER) to pulmonary function testing (PFT) in assessing idiopathic pulmonary fibrosis (IPF) for...
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