COPD

Exploring AI and ML in managing overlap between cardiovascular disease and asthma or COPD: a scoping review.

Cardiovascular disease (CVD) is a major comorbidity in asthma and chronic obstructive pulmonary disease (COPD), yet the contribution of artificial intelligence (AI) and machine learning (ML) to CVD risk assessment and management in these conditions remains insufficiently characterized. This scoping review identified the main original full-text studies applying AI/ML to the overlap between CVD and ...

Clinical decision support system for breathlessness.

PURPOSE OF REVIEW: This review summarizes high-level evidence on clinical decision support systems, both more classical rules-based and emerging artificial intelligence-based examples. It discusses their potential and concerns, how to evaluate them and describes future directions based on published evidence, clinical experience and broader experience working with others in this space. RECENT FINDI...

Evaluating the quality of online health information: A comparative study of COPD patient information in Facebook forums versus ChatGPT.

BACKGROUND: Patients with chronic obstructive pulmonary disease (COPD) increasingly turn to online platforms for health information. However, the qual...

A novel machine learning model of smartphone-based 1-minute sit-to-stand test for prediction of six-minute walk test distance in patients with COPD.

BACKGROUND: Regular assessment of exercise tolerance is essential for managing COPD, nevertheless, the standard 6-Minute Walk Test (6MWT) is difficult...

Synthetic data-augmented machine learning for 30-day readmission prediction in patients with chronic conditions: a retrospective real-world study.

OBJECTIVES: To develop and evaluate an explainable machine learning framework enhanced with synthetic data generation to predict unplanned 30-day hosp...

Human versus artificial intelligence: evaluating ChatGPT's performance in conducting published systematic reviews with meta-analysis in chronic pain research.

INTRODUCTION: Artificial intelligence (AI), particularly large-language models like Chat Generative Pre-Trained Transformer (ChatGPT), has demonstrate...

Atomic-resolution imaging of gold species at organic liquid-solid interfaces.

The structure and dynamics of adsorbed atoms (adatoms) at solid-liquid interfaces determine the performance of advanced catalysts, electrochemical dev...

Machine Learning Optimization of Laser Ablation in Liquid for the Green and Low-Cost Synthesis of Clean Gold Nanoparticles.

While gold nanoparticles (Au NPs) are widely employed in modern technology, their large-scale synthesis still faces challenges related to cost and sus...

Deep Learning Segmentation of Pectoralis Muscle Volume at CT and Comparison with Pectoralis Muscle Area in COPD.

Purpose To develop a deep learning model for segmenting pectoralis muscle volume (PMV) at CT and evaluate the reproducibility, group differences, and ...

A cough sound-based deep learning algorithm for accessible prompt detection of chronic obstructive pulmonary disease with smartphones.

Early COPD diagnosis is vital for effective management, yet conventional tools such as professional spirometers are often inaccessible in resource-lim...

Benchmarking Hybrid CNN-Transformer Versus Pure Transformer Architectures for Accelerated Hyperpolarized 129Xe MRI Reconstruction.

BACKGROUND: Hyperpolarized 129Xe MRI faces technical challenges including low signal-to-noise ratio and breath-hold constraints. Current literature fo...

Toward Opioid-Free Ambulatory Surgery: A Prospective Study Using Machine Learning to Predict Postoperative Opioid Use.

BACKGROUND: Postoperative opioid use has the risk of dependence and diversion. We developed an opioid-sparing regimen and identified factors associate...

Artificial intelligence-assisted FTIR spectroscopy for hormone receptor subtyping in formalin-fixed breast Cancer tissues.

BACKGROUND: Determination of estrogen receptor (ER) and progesterone receptor (PR) status is critical for breast cancer subtyping and guiding endocrin...

A Multi-Scale Hybrid Efficient Deep Learning Model for COPD Detection Using Respiratory Sounds.

Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory disease, and early diagnosis is crucial for timely intervention and improved p...

Overall risk of cancer incidence attributable to adult body CT examinations: impact of a seven-year continuous quality improvement program.

OBJECTIVES: To estimate the impact of a continuous dose reduction and quality improvement program on radiation-induced cancer risk in adult computed t...

Identifying Undiagnosed COPD Using Machine Learning-Based Classification.

BACKGROUND: COPD is a leading cause of morbidity and mortality worldwide. However, 80% of individuals with COPD are undiagnosed, leading to accelerate...

Integrated ore classification using stand-alone and hybridised machine learning algorithms.

A state-of-the-art, robust classification model using artificial intelligence (AI) algorithms was developed in this study to estimate the gold ore cla...

Accurate segmentation of pulmonary arteries and veins via a human-in-the-loop framework with application in COPD.

HOW GENETICS CHANGED OR WILL CHANGE THE THERAPY IN THYROID NODULES WITH INDETERMINATE CYTOLOGY.

The incidence of thyroid cancer has risen in recent decades, largely due to the widespread use of increasingly sensitive imaging techniques that have ...

Endothelial cell senescence shapes T cell activity in late-stage of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a leading cause of death with few effective therapies. While clinical staging distinguishes mild to ve...