Latest AI and machine learning research in pulmonology for healthcare professionals.
BACKGROUND: Bronchiolitis is a leading cause of hospitalization in infants, yet early and accurate risk prediction remains a clinical challenge. Traditional models often lack the complexity to capture nonlinear interactions or the transparency required for clinical trust. OBJECTIVE: This multicenter study aimed to develop, validate, and interpret machine learning (ML) models for predicting bronchi...
Early detection of lung cancer remains one of the most effective strategies for improving survival; however, diagnostic performance is limited by variability in imaging protocols, scanner settings, lesion characteristics, and inter-reader interpretation. Deep learning (DL) models enable automated feature representation from medical images, while radiomics provides interpretable handcrafted biomark...
BACKGROUND: Ventilator-induced diaphragm dysfunction (VIDD) is a frequent and under-recognized consequence of prolonged mechanical ventilation in inte...
Patient-specific computational tools hold great promise for the development of more personalized treatment strategies for acute respiratory failure. S...
Ultrafast and stable steady-state temperature perception is critically important for emerging applications such as electronic skin and intelligent hum...
Mycoplasma pneumoniae pneumonia (MPP) is a respiratory infection that readily propagates within pediatric populations, and thus, the development of a ...
Progressive pulmonary fibrosis (PPF) remains difficult to predict because static imaging may not fully capture regional respiratory motion, ventilatio...
BACKGROUND: Low peak oxygen consumption (V̇O2) is associated with higher cardiovascular and all-cause mortality, while improvements in peak V̇O2 reduc...
While deep learning has advanced the automated diagnosis of pulmonary diseases from chest X-rays, transitioning these models to treatment optimisation...
BACKGROUND: Predicting successful heart donation after circulatory death (DCD) remains a challenge. We developed a model to predict progression to cir...
OBJECTIVES: To systematically map the extent and nature of research on AI-enhanced point-of-care (POC) and rapid diagnostic technologies for infectiou...
Large language models can synthesize biomedical knowledge, parse vast amounts of data, and generate code, positioning them as promising tools for biom...
High-dimensional medical data hinder predictive modeling because of noise and the curse of dimensionality, making robust feature selection (FS) essent...
As a low-dose portable imaging technology, chest X-ray (CXR) is widely used for the screening of lung diseases, including COVID-19. However, existing ...
BACKGROUND: Ferroptosis plays a significant role in pulmonary arterial hypertension (PAH), although its underlying mechanisms and key pathogenic genes...
Rapid urbanization, migration and climate change are accelerating the appearance and diversification of respiratory viruses, overwhelming the pace at ...
BACKGROUND: Pneumonia is a common critical illness in the intensive care unit (ICU), and a subset of patients rapidly progresses to respiratory failur...
BACKGROUND: Intracranial steno-occlusive lesions are characteristic of moyamoya disease (MMD), but increasing reports of extracranial vascular involve...
ObjectiveTo develop a predictive model for estimating cortical bone thickness at any maxillary location in patients with unilateral cleft lip and pala...
OBJECTIVES: To benchmark medical image-specific vision-language models (VLMs) against real-world radiologist-written reports, focusing on diagnostic q...