Radiomics is a rapidly developing field of research focused on the extraction of quantitative
features from medical images, thus converting these digital images into minable, high …

Background Machine learning and deep learning models have been increasingly used to
predict long-term disease progression in patients with chronic obstructive pulmonary …

Recently, interest and advances in artificial intelligence (AI) including deep learning for
medical images have surged. As imaging plays a major role in the assessment of pulmonary …

Background Chronic obstructive pulmonary disease (COPD), a preventable lung disease,
has the highest prevalence in the elderly and deserves special consideration regarding …

Chronic obstructive pulmonary disease (COPD) is a preventable, treatable, progressive
chronic disease characterized by persistent airflow limitation. Patients with COPD deserve …

Personalized prediction of chronic diseases is crucial for reducing the disease burden.
However, previous studies on chronic diseases have not adequately considered the …

Background Computed tomography (CT) plays a great role in characterizing and quantifying
changes in lung structure and function of chronic obstructive pulmonary disease (COPD) …

Introduction Because of persistent airflow limitation in chronic obstructive pulmonary disease
(COPD), patients with COPD often have complications of dyspnea. However, as a leading …

Backgrounds The respiratory microbiota and radiomics correlate with the disease severity
and prognosis of chronic obstructive pulmonary disease (COPD). We aim to characterize the …

Background Chronic obstructive pulmonary disease (COPD) is a frequently diagnosed yet
treatable condition, provided it is identified early and managed effectively. This study aims to …