Pulmonology

Artificial intelligence for lung cancer: a systematic review of head‑to‑head CT, FDG PET/CT, and multimodal models across screening, staging, and prognosis.

BACKGROUND: Artificial intelligence (AI) has shown increasing potential in lung cancer imaging, particularly in detection, staging, prognosis, and recurrence prediction. However, there is limited synthesis of head-to-head comparative evidence between CT, FDG PET/CT, and multimodal fusion models within the same cohorts. OBJECTIVES: To systematically review and critically appraise studies that direc...

[Application of a novel robot-assisted navigation system in CT-guided percutaneous lung biopsy].

Objective: To compare the clinical efficacy and safety of robot-assisted navigation systems with those of the conventional puncture localization method in CT-guided percutaneous lung biopsy. Methods: We retrospectively collected clinical data from 140 patients who underwent CT-guided percutaneous lung biopsy at the Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Jiangh...

Performance of adult-trained artificial intelligence models in paediatric imaging-a scoping review.

OBJECTIVES: This scoping review aims to evaluate the performance of artificial intelligence (AI) models designed for adults when applied to paediatric...

Leveraging natural language processing and machine learning to identify chronic conditions from primary care electronic medical records.

Primary care electronic medical records (EMRs) contain rich data that can support proactive identification of chronic health conditions. However, leve...

Machine learning-based on model for explain risk of 24-hour death in critically ill patients in the prehospital setting: A retrospective cohort study.

This study aimed to develop and validate a machine learning-based model for predicting 24-hour mortality in critically ill patients using prehospital ...

A rapid diagnostic approach for COPD utilizing multimodal serum spectra integrated with machine learning algorithms.

Chronic Obstructive Pulmonary Disease (COPD) is a major global respiratory illness causing death and disability. Traditional methods lack consistent s...

A deep learning model based on ultrasound imaging to differentiate malignant from benign pleural effusion: a multicenter cohort study.

Noninvasive Staging of Hepatic Fibrosis in Patients with Autoimmune Liver Disease Using Deep Learning.

RATIONALE AND OBJECTIVES: Accurate staging of hepatic fibrosis is essential for guiding immunosuppressive and antifibrotic therapies. However, percuta...

Advances in nanostructured chemiresistive sensors for formaldehyde detection.

Formaldehyde (HCHO) is deleterious both as an indoor volatile organic compound, contributing to respiratory and carcinogenic risks, and as an adultera...

A Large Language Model Approach to Functional Status Scale Assessment.

OBJECTIVES: To develop a fine-tuned version of the generative pretrained transformer (GPT)-4o artificial intelligence (AI) model able to estimate Func...

Artificial Intelligence-Assisted Identification and Prevention of Chronic Obstructive Pulmonary Disease Using Biodegradable and Reusable Piezoelectric Elastomer/Poly(l-lactic acid) Composite Nanofiber Membrane.

Chronic obstructive pulmonary disease (COPD) is a respiratory disease imposing significant economic and health burdens to patients. The long latent pe...

Multi-modal AI for opportunistic screening, staging and progression risk stratification of steatotic liver disease.

The global rise in steatotic liver disease poses a significant public health challenge. While non-contrast computed tomography scans hold promise for ...

Polysomnography Dataset for Sleep Analysis in Ischemic Stroke Patients.

Sleep architecture and integrity significantly influence neural recovery and cognitive restoration. These are particularly relevant in ischemic stroke...

HMI-LUSC: A Histological Hyperspectral Imaging Dataset for Lung Squamous Cell Carcinoma.

Hyperspectral imaging (HSI) is a three-dimensional imaging technique that integrates spectroscopy and imaging. When combined with microscopy, hyperspe...

Periodontitis Prediction Model Using Linked Electronic Health and Dental Records.

INTRODUCTION: Periodontal disease (PD) is closely linked to systemic health, with established associations with chronic conditions (eg, diabetes, card...

Exploring the toxicological mechanisms of Benzo[a]anthracene (BaA) exposure in lung adenocarcinoma (LUAD) via network toxicology, machine learning, and multi-dimensional bioinformatics analysis.

BACKGROUND: Lung adenocarcinoma (LUAD) is a major lung cancer subtype influenced by environmental factors. Benzo[a]anthracene (BaA), a common Group 2B...

Artificial intelligence and diagnosis and management of tuberculosis disease in children.

PURPOSE OF REVIEW: The literature review is pertinent because diagnosing pediatric tuberculosis (PdTB) remains quite challenging, especially in areas ...

Unraveling the matrix stiffness landscape in idiopathic pulmonary fibrosis: GSN and ARG1 as novel diagnostic biomarkers and potential therapeutic targets.

BACKGROUND: Idiopathic Pulmonary Fibrosis (IPF) is a progressive and fatal interstitial lung disease characterized by excessive extracellular matrix (...

Photoswitches for ion channel regulation: expanding the scope of phototherapy through computational chemistry.

The development of ion channel phototherapy using azobenzene-based photoswitchable molecules represents a promising strategy for the precise modulatio...

Identification and validation of the protective gene BCAT2 related to amino acid metabolism in idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease, with unknown pathogenesis and no effective treatment. Identifying the key...