AIMC Topic: Spirometry
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Deep learning for detecting and early predicting chronic obstructive pulmonary disease from spirogram time series.
NPJ systems biology and applications
Feb 15, 2025
Chronic Obstructive Pulmonary Disease (COPD) is a chronic lung condition characterized by airflow obstruction. Current diagnostic methods primarily rely on identifying prominent features in spirometry (Volume-Flow time series) to detect COPD, but the...
Transfer learning in spirometry: CNN models for automated flow-volume curve quality control in paediatric populations.
Computers in biology and medicine
Nov 13, 2024
PROBLEM: Current spirometers face challenges in evaluating acceptability criteria, often requiring manual visual inspection by trained specialists. Automating this process could improve diagnostic workflows and reduce variability in test assessments.
Quantitative CT Imaging Features Associated with Stable PRISm using Machine Learning.
Academic radiology
Aug 26, 2024
RATIONALE AND OBJECTIVES: The structural lung features that characterize individuals with preserved ratio impaired spirometry (PRISm) that remain stable overtime are unknown. The objective of this study was to use machine learning models with compute...
Machine learning for accurate detection of small airway dysfunction-related respiratory changes: an observational study.
Respiratory research
Jul 24, 2024
BACKGROUND: The use of machine learning(ML) methods would improve the diagnosis of small airway dysfunction(SAD) in subjects with chronic respiratory symptoms and preserved pulmonary function(PPF). This paper evaluated the performance of several ML a...
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 ...
Comparing performance of primary care clinicians in the interpretation of SPIROmetry with or without Artificial Intelligence Decision support software (SPIRO-AID): a protocol for a randomised controlled trial.
BMJ open
Jul 1, 2024
INTRODUCTION: Spirometry is a point-of-care lung function test that helps support the diagnosis and monitoring of chronic lung disease. The quality and interpretation accuracy of spirometry is variable in primary care. This study aims to evaluate whe...
Curve-Modelling and Machine Learning for a Better COPD Diagnosis.
International journal of chronic obstructive pulmonary disease
Jun 12, 2024
BACKGROUND: Development of new tools in artificial intelligence has an outstanding performance in the recognition of multidimensional patterns, which is why they have proven to be useful in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD...
Novel Machine Learning Identifies 5 Asthma Phenotypes Using Cluster Analysis of Real-World Data.
The journal of allergy and clinical immunology. In practice
Apr 27, 2024
BACKGROUND: Asthma classification into different subphenotypes is important to guide personalized therapy and improve outcomes.
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 ...
Machine Learning and CT Texture Features in Ex-smokers with no CT Evidence of Emphysema and Mildly Abnormal Diffusing Capacity.
Academic radiology
Dec 30, 2023
RATIONALE AND OBJECTIVES: Ex-smokers without spirometry or CT evidence of chronic obstructive pulmonary disease (COPD) but with mildly abnormal diffusing capacity of the lungs for carbon monoxide (DL) are at higher risk of developing COPD. It remains...
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