AIMC Topic: Spirometry

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Boosting K-nearest neighbor regression performance for longitudinal data through a novel learning approach.

BMC bioinformatics
BACKGROUND: Longitudinal studies often require flexible methodologies for predicting response trajectories based on time-dependent and time-independent covariates. To address the complexities of longitudinal data, this study proposes a novel extensio...

Potential effects of endocrine-disrupting chemicals on preserved ratio impaired spirometry revealed by five different approaches.

Ecotoxicology and environmental safety
OBJECTIVE: Evidence from prior studies indicates that certain endocrine-disrupting chemicals (EDCs), such as phenols and phthalates, may serve as environmental risk factors for chronic obstructive pulmonary disease (COPD). However, no studies have ex...

Exploring the potential associations between single and mixed volatile compounds and preserved ratio impaired spirometry using five different approaches.

Ecotoxicology and environmental safety
BACKGROUND: Although the relationship between environmental pollutants and respiratory health has received widespread attention, no studies have explored the association between volatile organic compounds (VOCs) and preserved ratio impaired spirometr...

Deep learning for detecting and early predicting chronic obstructive pulmonary disease from spirogram time series.

NPJ systems biology and applications
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
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
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
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
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
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
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...