Machine learning and deep learning predictive models for long-term prognosis in patients with chronic obstructive pulmonary disease: a systematic review and meta …
Background Machine learning and deep learning models have been increasingly used to
predict long-term disease progression in patients with chronic obstructive pulmonary …
predict long-term disease progression in patients with chronic obstructive pulmonary …
[HTML][HTML] Overcoming the challenges in the development and implementation of artificial intelligence in radiology: a comprehensive review of solutions beyond …
Artificial intelligence (AI) in radiology is a rapidly developing field with several prospective
clinical studies demonstrating its benefits in clinical practice. In 2022, the Korean Society of …
clinical studies demonstrating its benefits in clinical practice. In 2022, the Korean Society of …
AI improves nodule detection on chest radiographs in a health screening population: a randomized controlled trial
Background The impact of artificial intelligence (AI)–based computer-aided detection (CAD)
software has not been prospectively explored in real-world populations. Purpose To …
software has not been prospectively explored in real-world populations. Purpose To …
Enabling chronic obstructive pulmonary disease diagnosis through chest X-rays: A multi-site and multi-modality study
Purpose Chronic obstructive pulmonary disease (COPD) is one of the most common chronic
illnesses in the world. Unfortunately, COPD is often difficult to diagnose early when …
illnesses in the world. Unfortunately, COPD is often difficult to diagnose early when …
Deep learning enables automatic adult age estimation based on CT reconstruction images of the costal cartilage
T Lu, Y Diao, X Tang, F Fan, Z Peng, M Zhan, G Liu… - European …, 2023 - Springer
Objective Adult age estimation (AAE) is a challenging task. Deep learning (DL) could be a
supportive tool. This study aimed to develop DL models for AAE based on CT images and …
supportive tool. This study aimed to develop DL models for AAE based on CT images and …
CT whole lung radiomic nomogram: a potential biomarker for lung function evaluation and identification of COPD
TH Zhou, XX Zhou, J Ni, YQ Ma, FY Xu, B Fan… - Military Medical …, 2024 - Springer
Background Computed tomography (CT) plays a great role in characterizing and quantifying
changes in lung structure and function of chronic obstructive pulmonary disease (COPD) …
changes in lung structure and function of chronic obstructive pulmonary disease (COPD) …
Deep learning-based prognostication in idiopathic pulmonary fibrosis using chest radiographs
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 …
idiopathic pulmonary fibrosis (IPF) using chest radiographs. Methods To develop a deep …
A deep learning model using chest radiographs for prediction of 30-day mortality in patients with community-acquired pneumonia: development and external …
BACKGROUND. Chest radiography is an essential tool for diagnosing community-acquired
pneumonia (CAP), but it has an uncertain prognostic role in the care of patients with CAP …
pneumonia (CAP), but it has an uncertain prognostic role in the care of patients with CAP …
[HTML][HTML] Survey on Value Elements Provided by Artificial Intelligence and Their Eligibility for Insurance Coverage With an Emphasis on Patient-Centered Outcomes
H Jhang, SJ Park, AR Sul, HY Jang… - Korean Journal of …, 2024 - ncbi.nlm.nih.gov
Objective This study aims to explore the opinions on the insurance coverage of artificial
intelligence (AI), as categorized based on the distinct value elements offered by AI, with a …
intelligence (AI), as categorized based on the distinct value elements offered by AI, with a …
Novel Lobe-based Transformer model (LobTe) to predict emphysema progression in Alpha-1 Antitrypsin Deficiency
AH Curiale, RSJ Estépar - Computers in Biology and Medicine, 2025 - Elsevier
Emphysema, marked by irreversible lung tissue destruction, poses challenges in
progression prediction due to its heterogeneity. Early detection is particularly critical for …
progression prediction due to its heterogeneity. Early detection is particularly critical for …