Pulmonology

Hybrid supervised deep learning for lung adenocarcinoma diagnosis to optimize surgical strategies.

Intraoperative frozen section pathological diagnosis of lung adenocarcinoma serves as the gold standard for determining the extent of surgical resection. Due to the dual constraints of intraoperative time limitations and the challenge of manually assessing tumor invasion volume in three-dimensional space, current manual diagnostic approaches and weakly supervised deep learning methods have demonst...

Development of machine learning and nomogram models to predict lung metastasis and prognosticate survival in breast cancer.

PURPOSE: Lung metastasis in breast cancer (BCLM) is a critical determinant of poor prognosis, occurring in approximately 30-50% of advanced cases and associated with significantly reduced median survival. This study aimed to develop machine learning models for predicting BCLM and evaluating prognosis using the SEER database. METHODS: Data from the SEER database (2018-2021) were analyzed. For the p...

Cauchy Lotus Optimization-based feature selection and ResNet 101 based XceptionNet architecture for radiation pneumonitis prediction in lung cancer patients.

Thoracic radiotherapy for lung cancer patients followed by radiation pneumonitis (RP) has significant clinical side effects. Risk-adaptive treatment p...

Artificial intelligence (AI)-assisted ultrasound in clinical trials: Endpoint automation, decentralized monitoring, and regulatory readiness.

Ultrasound is among the most widely used imaging modalities in clinical trials, and yet its dependence on operator skill and equipment settings has hi...

Combining cutting edge computational and experimental methods for targeting kras mutations in non-small cell lung cancer.

INTRODUCTION: Historically, KRAS mutations have been notoriously difficult to target despite their status as the most commonly mutated oncogene in the...

A Transformer-ResNet-Integrated Deep Learning Model for Digital Pathology-Based Grading and Risk Stratification of MASLD-Related Liver Fibrosis.

INTRODUCTION: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects up to 30% of the global population and drives progression to fi...

A Roadmap to Transform Lung Cancer Outcomes: Priorities in Biology, Therapeutic Innovation, Early Detection, Prevention and Interception.

Advances in targeted therapies, immunotherapy, and early detection have revolutionized lung cancer treatment and extended survival. Nonetheless, lung ...

Effective elimination of respiratory misregistration-induced attenuation correction errors in PET/CT via deep learning trained on data-driven gated PET from strictly respiratory-phase-matched PET/CT cases.

Pre-Imaging Clinical Factors Associated With Cardiac MR Image Quality Using Large Language Model-Enabled Data Extraction.

BACKGROUND: Poor cardiac MR image quality can prompt repeat examinations and hinder clinical decision-making. PURPOSE: To evaluate whether pre-imaging...

A motor thalamic site in humans that suppresses involuntary breathing without awareness.

Breathing is generated by brainstem respiratory networks but can be controlled and modulated by forebrain activity. The recent clinical adoption of th...

Advances in Oral Cavity Stem Cell Research Revealed through Multi-omics Analysis.

Oral stem cell research encompasses the study of dental pulp stem cells, periodontal ligament stem cells, regeneration of dental pulp and periodontal ...

Deep learning-based segmentation of enamel, cementum, alveolar bone, and gingiva in periodontal ultrasound images.

OBJECTIVES: To develop a deep learning-based multi-class segmentation model for the simultaneous segmentation of key periodontal structures, including...

AttnEffNet-B4: an attention-augmented EfficientNet-B4 framework with fourier transformation for robust multi-disease diagnosis.

Early and precise disease detection in healthcare plays a vital role for better treatment results, healthier life expectancy, and good quality of care...

A noninvasive urinary microRNA-based assay for early detection of lung cancer and its potential application to prognosis and recurrence monitoring: a case-control study.

Lung cancer remains the leading cause of cancer-related mortality worldwide, with recurrence or cancer-related death occurring even after curative-int...

Investigation of the use of urinary proteomics in the prediction of childhood asthma.

PURPOSE: Urinary proteomics may help us improve our understanding and classification of asthma. We sought to identify clusters of children based on ur...

Molecular modelling-driven formulation design for targeted pulmonary drug delivery.

Molecular modelling an impactful and trending approach for rational design of pulmonary drug delivery systems. In particular, in silico techniques can...

Chest Tube Learning Synthesis and Evaluation Assistant (CheLSEA): A Prospective Observational Trial of an Intelligent Decision Support System.

OBJECTIVE: This study evaluates the performance of an artificial intelligence predictive clinical decision support system (CheLSEA) in generating ches...

Non-invasive assessment of left atrial pressure in patients with heart failure: head to head comparison of novel machine-learning based echocardiographic tool with a wireless pulmonary artery sensor.

Macrophage polarization as a therapeutic target in lung diseases: From pathogenesis to precision intervention.

Macrophages serve as core effector cells of the innate immune system, exerting dual regulatory roles in pulmonary homeostasis maintenance and disease ...

Construction of Rheumatoid Arthritis-Associated Interstitial Lung Disease diagnostic model and identification of biomarkers based on a multi-omics integration strategy of machine learning.

OBJECTIVE: This study aimed to develop and validate a machine learning model integrating multi-omics and radiomics data to improve diagnostic accuracy...