Background: Idiopathic pulmonary fibrosis (IPF) needs a precise prediction method for its
prognosis. This study took advantage of artificial intelligence (AI) deep learning to develop a …

Few diseases are hard to detect and life-threatening as well, and Pulmonary Fibrosis (PF) is
one of them. PF is a chronic disorder that leads to progressive scarring of the lungs, and we …

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 …

Lung fibrosis means scarring of tissue in a patient's lungs and is a common condition that
can complicate the course of COVID-19 disease. Pulmonary fibrosis destroys the patient's …

Objectives To develop and validate a deep learning-based prognostic model in patients with
idiopathic pulmonary fibrosis (IPF) using chest radiographs. Methods To develop a deep …

Background Idiopathic pulmonary fibrosis (IPF) is the most common idiopathic interstitial
lung disease. Clinical models to accurately evaluate the prognosis of IPF are currently …

Machine Learning (ML) is an algorithm based on big data, which learns patterns from the
previously observed data through classifying, predicting, and optimizing to accomplish …

Objective. To develop and validate a risk assessment model for the prediction of the acute
exacerbation of idiopathic pulmonary fibrosis (AE‐IPF) in patients with idiopathic pulmonary …

Idiopathic pulmonary fibrosis (IPF) is a fatal lung disease characterized by an unpredictable
progressive decline in lung function. Natural history of IPF is unknown and the prediction of …

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) …