Pulmonology

Physiological-model-based neural network for modeling the metabolic-heart rate relationship during physical activities.

BACKGROUND AND OBJECTIVE: Heart failure (HF) poses a significant global health challenge, with early detection offering opportunities for improved outcomes. Abnormalities in heart rate (HR), particularly during daily activities, may serve as early indicators of HF risk. However, existing HR monitoring tools for HF detection are limited by their reliability on population-based averages. The estimat...

Sleep apnoea and its consequences: from animal models to precision medicine.

A European Respiratory Society research seminar entitled "Sleep Apnoea and Its Consequences: From Animal Models to Precision Medicine" was held in January 2024 in Lisbon, Portugal. It provided an in-depth analysis of the current landscape and future directions in OSA research, integrating recent findings from metabolomics, animal models, clinical predictors of cardiometabolic consequences of OSA, ...

Machine learning models for predicting postoperative complications following mandibular third molar surgery: Development, validation, and explainable AI insights.

The surgical removal of impacted mandibular third molars is a routine procedure in oral and maxillofacial surgery but is consistently associated with ...

Comparative analysis of five AI platforms for mandibular canal segmentation on CBCT images.

OBJECTIVES: Accurate mandibular canal (MC) identification on cone-beam computed tomography (CBCT) is vital to prevent inferior alveolar nerve injury d...

Epidemiologic trajectories and burden of multidrug-resistant tuberculosis (MDR-TB) mortality across South Asia: An analysis of Global Burden of Disease data (1990-2023) with machine learning forecasting to 2050.

BACKGROUND: Multidrug-resistant tuberculosis (MDR-TB) remains a major public health challenge in South Asia, which bears a disproportionate global bur...

Automated CT-derived body composition predicts pathologic response to neoadjuvant immunotherapy in non-small cell lung cancer.

Tumor-intrinsic biomarkers alone insufficiently predict pathological complete response (pCR) to neoadjuvant immunochemotherapy (NICT) in non-small cel...

Integrating Mendelian randomization and multi-omics analysis unravels gut microbiota-driven metabolic mechanisms in sepsis and identifies diagnostic biomarkers through experimental validation.

Sepsis, a life-threatening systemic inflammatory syndrome, remains a leading cause of global mortality due to its complex pathophysiology and the lack...

Single‑cell mapping of neutrophil extracellular trap signatures in lung adenocarcinoma reveals immune landscapes, prognostic potential, and therapeutic targets.

Neutrophil extracellular traps (NETs) have emerged as key modulators in the tumor microenvironment, yet their cellular heterogeneity, molecular mechan...

From bench to bedside: The clinical relevance of atrial electrical remodeling in atrial fibrillation therapy.

Atrial electrical remodeling spans molecular, electrical, and structural alterations that shorten refractoriness, facilitate reentry, and ultimately c...

ASO Author Reflections: Artificial Intelligence-Driven Thoracoscopic Video Analysis for Intraoperative Visceral Pleural Invasion Prediction.

Elucidating hydrogen bonding and synergistic adsorption mechanisms of morphine on deep eutectic solvent-functionalized biochar through machine learning and density functional theory.

Adsorbent materials effectively separated psychoactive substances from the ambient medium through adsorption, serving as a sustainable removal strateg...

Rapid Free-Breathing and Automated 2D Shimming of the Lung at 3T.

PURPOSE: To develop and validate a rapid, fully automated method for shimming of the lung. METHODS: For field mapping of the lung, a custom 2D RF spoi...

Multimodal Convolutional Neural Network Model for Evaluating Development of Fetal Rabbit Lung Using B-mode and Shear Wave Elastography Ultrasound Images.

OBJECTIVE: To evaluate the performance of convolutional neural network (CNN)-based models for predicting fetal rabbit lung development: unimodal model...

Co-classification network analysis reveals nodal dysfunction and dimension-specific alterations in obstructive sleep apnea-hypopnea syndrome.

BACKGROUND: Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a prevalent sleep disorder linked to brain alterations, but its brain network pattern...

A machine learning-driven app for predicting the need for post-operative respiratory support in liver transplant recipients.

BACKGROUNDS: Liver transplantation (LT) is a life-saving procedure for patients with end-stage liver disease, yet post-operative complications, partic...

The role of AI-driven communication in delirium prevention, detection, and care for critically ill ICU patients: A systematic review with inductive thematic synthesis.

BACKGROUND: Delirium remains one of the most consequential complications among critically ill patients in ICUs, exerting profound effects on morbidity...

SegRenal: AI-Driven segmentation of frozen sections in transplant kidney biopsies - A comparative analysis of deep learning models.

BACKGROUND AND OBJECTIVE: Frozen section evaluation of donor kidney biopsies is vital for determining transplant suitability, yet remains challenging ...

Deep Laplacian Coordinates: End-to-end deeply guided anisotropic diffusion for COVID-19 pulmonary lesion segmentation.

Despite notable advances in deep learning, accurately segmenting lung lesions in computed tomography remains a significant challenge due to the scarci...

Imaging Evaluation for Steatotic Liver Disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as nonalcoholic fatty liver disease, is the fastest-growing cause o...

Research progress and clinical utility of multi-parameter orbital MRI in thyroid-associated ophthalmopathy.

Thyroid-associated ophthalmopathy (TAO), the most common orbital disease in adults, is a specific autoimmune condition closely associated with thyroid...