AIMC Topic: Forced Expiratory Volume
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Machine-Learning-Based Computed Tomography Radiomics Regression Model for Predicting Pulmonary Function.
Academic radiology
Apr 10, 2025
RATIONALE AND OBJECTIVES: Chest computed tomography (CT) radiomics can be utilized for categorical predictions; however, models predicting pulmonary function indices directly are lacking. This study aimed to develop machine-learning-based regression ...
A deep learning-based model to estimate pulmonary function from chest x-rays: multi-institutional model development and validation study in Japan.
The Lancet. Digital health
Jul 8, 2024
BACKGROUND: Chest x-ray is a basic, cost-effective, and widely available imaging method that is used for static assessments of organic diseases and anatomical abnormalities, but its ability to estimate dynamic measurements such as pulmonary function ...
Diagnosis and Severity Assessment of COPD Using a Novel Fast-Response Capnometer and Interpretable Machine Learning.
COPD
Apr 24, 2024
INTRODUCTION: Spirometry is the gold standard for COPD diagnosis and severity determination, but is technique-dependent, nonspecific, and requires administration by a trained healthcare professional. There is a need for a fast, reliable, and precise ...
Artificial Intelligence-Based Emphysema Quantification in Routine Chest Computed Tomography: Correlation With Spirometry and Visual Emphysema Grading.
Journal of computer assisted tomography
Dec 18, 2023
OBJECTIVE: The aim of the study is to assess the correlation between artificial intelligence (AI)-based low attenuation volume percentage (LAV%) with forced expiratory volume in the first second to forced vital capacity (FEV1/FVC) and visual emphysem...
Deep Learning-based Approach to Predict Pulmonary Function at Chest CT.
Radiology
Feb 14, 2023
Background Low-dose chest CT screening is recommended for smokers with the potential for lung function abnormality, but its role in predicting lung function remains unclear. Purpose To develop a deep learning algorithm to predict pulmonary function w...
[Quantitative Evaluation of Airway Lesions in Chronic Obstructive Pulmonary Disease by Applying Deep Learning Reconstruction to Ultra-high-resolution CT Images: Correlation between Wall Area Percentage and Forced Expiratory Volume in One Second Percentage].
Nihon Hoshasen Gijutsu Gakkai zasshi
Aug 22, 2022
PURPOSE: Using ultra-high-resolution images reconstructed with the Advanced intelligent Clear-IQ Engine (AiCE) lung to measure wall area percentage (WA%), we demonstrated that WA% measured in more distal bronchus has a stronger correlation with respi...
Deep Learning Prediction of Survival in Patients with Chronic Obstructive Pulmonary Disease Using Chest Radiographs.
Radiology
Jun 7, 2022
Background Preexisting indexes for predicting the prognosis of chronic obstructive pulmonary disease (COPD) do not use radiologic information and are impractical because they involve complex history assessments or exercise tests. Purpose To develop a...
Covariate adjustment of spirometric and smoking phenotypes: The potential of neural network models.
PloS one
May 11, 2022
To increase power and minimize bias in statistical analyses, quantitative outcomes are often adjusted for precision and confounding variables using standard regression approaches. The outcome is modeled as a linear function of the precision variables...
Deep learning for spirometry quality assurance with spirometric indices and curves.
Respiratory research
Apr 21, 2022
BACKGROUND: Spirometry quality assurance is a challenging task across levels of healthcare tiers, especially in primary care. Deep learning may serve as a support tool for enhancing spirometry quality. We aimed to develop a high accuracy and sensitiv...
A Framework for Using Real-World Data and Health Outcomes Modeling to Evaluate Machine Learning-Based Risk Prediction Models.
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Dec 22, 2021
OBJECTIVES: We propose a framework of health outcomes modeling with dynamic decision making and real-world data (RWD) to evaluate the potential utility of novel risk prediction models in clinical practice. Lung transplant (LTx) referral decisions in ...
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