Pulmonology

Quality of Human Expert versus Large Language Model Generated Multiple Choice Questions in the Field of Mechanical Ventilation.

BACKGROUND: Mechanical ventilation (MV) is a critical competency in critical care training, yet stan...

Collaborative assessment of the risk of postoperative progression in early-stage non-small cell lung cancer: a robust federated learning model.

BACKGROUND: While the TNM staging system provides valuable insights into the extent of disease, pred...

Machine learning and discriminant analysis model for predicting benign and malignant pulmonary nodules.

BACKGROUND: Pulmonary Nodules (PNs) are a trend considered as the early manifestation of lung cancer...

Determination of lung cancer exhaled breath biomarkers using machine learning-a new analysis framework.

Exhaled breath samples of lung cancer patients (LC), tuberculosis (TB) patients and asymptomatic con...

Integrative multi-omics and machine learning reveal critical functions of proliferating cells in prognosis and personalized treatment of lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a major cause of cancer-related mortality globally. Proliferating cell...

A multimodal dataset for training deep learning models aimed at detecting and analyzing sleep apnea.

Sleep Apnea Syndrome (SAS) is a serious respiratory disorder that can lead to a range of complicatio...

AI Prognostication in Nonsmall Cell Lung Cancer: A Systematic Review.

The systematic literature review was performed on the use of artificial intelligence (AI) algorithms...

Research on lung cancer diagnosis based on machine learning.

BackgroundIn clinical diagnosis, determining the level of malignancy in tumors and differentiating b...

Non-invasive tests of fibrosis in the management of MASLD: revolutionising diagnosis, progression and regression monitoring.

With the recent conditional approval of resmetirom by the US Food and Drug Administration, the treat...

Shared pathogenic mechanisms linking obesity and idiopathic pulmonary fibrosis revealed by bioinformatics and in vivo validation.

Previous studies have suggested a potential correlation between obesity and idiopathic pulmonary fib...

FLPneXAINet: Federated deep learning and explainable AI for improved pneumonia prediction utilizing GAN-augmented chest X-ray data.

Pneumonia, a severe lung infection caused by various viruses, presents significant challenges in dia...

Machine Learning Prediction of Financial Toxicity in Patients with Resected Lung Cancer.

BACKGROUND: Financial toxicity (FT) refers to the financial stress and detrimental impact on quality...

On-Mask Magnetoelastic Sensor Network for Self-Powered Respiratory Monitoring.

Respiratory monitoring is crucial because it provides key insights into a person's health and physio...

A comprehensive machine learning for high throughput Tuberculosis sequence analysis, functional annotation, and visualization.

With human guidance, computers now use machine learning (ML) in artificial intelligence (AI) to lear...

A Machine Learning Approach to Differentiate Cold and Hot Syndrome in Viral Pneumonia Integrating Traditional Chinese Medicine and Modern Medicine: Machine Learning Model Development and Validation.

BACKGROUND: Syndrome differentiation in traditional Chinese medicine (TCM) is an ancient principle t...

Single Inspiratory Chest CT-based Generative Deep Learning Models to Evaluate Functional Small Airway Disease.

Purpose To develop a deep learning model that uses a single inspiratory chest CT scan to generate p...

Molecular mechanisms of efferocytosis imbalance in the idiopathic pulmonary fibrosis microenvironment: from gene screening to dynamic regulation analysis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive pulmonary disease character...

Assessing inflammatory protein biomarkers in COPD subjects with and without alpha-1 antitrypsin deficiency.

RATIONALE: Individuals homozygous for the Alpha-1 Antitrypsin (AAT) Z allele (Pi*ZZ) exhibit heterog...

Non-invasive liver fibrosis screening on CT images using radiomics.

PURPOSE: To develop a radiomics machine learning model for detecting liver fibrosis on CT images of ...

Performance of a screening-trained DL model for pulmonary nodule malignancy estimation of incidental clinical nodules.

OBJECTIVE: To test the performance of a DL model developed and validated for screen-detected pulmona...

Artificial Intelligence Moving Into Respiratory Medicine.