Pulmonology

LungNet: Leveraging state-space models with SE-enhanced skip connections for precise CT-based lung lesion segmentation.

Lung cancer, which accounted for 2.48 million new cases and 1.82 million deaths worldwide in 2022, continues to be the most lethal cancer across the globe, underscoring the urgent demand for more advanced diagnostic tools. Although computed tomography (CT) imaging has long been central to lung cancer detection, the heterogeneous and complex characteristics of lung lesions make accurate segmentatio...

Towards interpretable AI in personalized medicine through a radiological-biological radiomics dictionary linking semantic Lung-RADS and imaging radiomics features.

BACKGROUND: Lung cancer remains the leading cause of cancer-related mortality worldwide, with survival largely dependent on early detection. Standard-dose computed tomography (CT) screening, guided by the Lung Imaging Reporting and Data System (Lung-RADS), provides standardized criteria for nodule evaluation. However, interpretation is limited by inter-reader variability and reliance on qualitativ...

Decoupling lactylation-associated metabolic remodelling in Asthma: Integrated multi-omics and machine learning identify RCC2 as a potential therapeutic target.

BACKGROUND: Aerobic glycolysis promotes lactate accumulation and histone lactylation (Kla), yet the cell-type-specific distribution of this axis and i...

Construction and interpretability evaluation of a prediction model for radiographic pneumonia in children at outpatient and emergency departments.

BACKGROUND: Radiographic confirmation is crucial for pediatric pneumonia diagnosis, but chest X-ray overuse in outpatient and emergency settings raise...

MUSIOMICS: A multi-region radiomics framework that outperforms single-region analysis in classifying malignant pulmonary nodules.

BACKGROUND AND OBJECTIVE: Radiomic studies in lung cancer have primarily analyzed single-domain features extracted separately from intranodular (Zone-...

Establishment of prediction equations for available energy values of sorghum in broilers using machine learning and stepwise regression methods.

This study aimed to determine the available energy values of sorghum for Arbor Acres (AA) broilers and to develop and compare prediction equations usi...

Fluid Volumes Longitudinal Modeling to Predict Atrophy and Fibrosis in Neovascular Age-Related Macular Degeneration.

PURPOSE: To evaluate the impact of retinal fluid volumes on the development of atrophy and fibrosis in neovascular age-related macular degeneration (n...

Natural bioactive as modulators of airway inflammation and remodeling: mechanistic insights.

Airway diseases such as asthma, COPD, pulmonary fibrosis, and other inflammatory airway conditions remain a significant threat to global health. Tradi...

Serum mass spectral fingerprints with machine learning for early discrimination of infectious pneumonia in the emergency department.

Lung cancer diagnosis from CT scans using artificial intelligence techniques: A global perspective.

OBJECTIVE: In this research, we conducted a systematic review of artificial intelligence techniques used for the diagnosis of lung cancer. METHODS: A ...

Epigenetic Instability-Based Metrics in Cell-Free DNA for Early Cancer Detection.

PURPOSE: Cancers present significant DNA methylation changes, which arise in a stochastic manner, marked by extensive epigenetic variation, indicative...

Update on pleural mesothelioma.

PURPOSE OF REVIEW: Pleural mesothelioma remains a universally lethal cancer with a rising global burden. This underscores the need for pulmonologists ...

HP-DIL: Deep heterogeneity profiling with graph-informed disentangled interaction learning for MRI-based liver fibrosis staging.

Liver fibrosis staging (LFS) informs treatment decisions and prognostic assessment in liver disease. Multiparametric MRI enables non-invasive, quantit...

Augmenting Large Language Model With Prompt Engineering and Supervised Fine-Tuning in Non-Small Cell Lung Cancer Tumor-Node-Metastasis Staging: Framework Development and Validation.

BACKGROUND: Accurate tumor node metastasis (TNM) staging is fundamental for treatment planning and prognosis in non-small cell lung cancer (NSCLC). Ho...

Research on Risk Transfer Pathways for Lung Cancer Among Middle-Aged and Older Individuals Using Deep Reinforcement Learning: Retrospective Cohort Study.

BACKGROUND: Nowadays, lung cancer has a significantly high incidence rate worldwide. The mortality rate of lung cancer continues to rise; it is more c...

[Comparative observation of analgesic efficacy between liposomal bupivacaine and "cocktail" therapy following artificial intelligence-assisted direct anterior approach total hip arthroplasty: A prospective randomized controlled study].

OBJECTIVE: To compare the analgesic efficacy and safety of liposomal bupivacaine (LB) versus ropivacaine for surgical incision local anesthesia after ...

Bioinformatics analysis and qRT-PCR validation of iron metabolism-related genes in pediatric asthma.

Pediatric asthma (PA) is a chronic airway disease with a complex etiology, and iron metabolism disorder is believed to be involved in its pathogenesis...

An algorithm to identify less invasive surfactant administration using a real-world database of preterm infants.

BACKGROUND: Surfactant replacement therapy is central to respiratory distress syndrome (RDS) management in preterm infants, which can be delivered usi...

An intelligent fusion model for Ki-67 prediction in non-small cell lung cancer: A cloud-based prediction system integrating radiomics.

BACKGROUND: The expression level of Ki-67 affects the prognosis of NSCLC patients. OBJECTIVE: Accurate preoperative prediction of Ki-67 expression in ...

Clinical accuracy and applications of the Pediatric Assessment Triangle in emergency care: a narrative review.

BACKGROUND: The Pediatric Assessment Triangle (PAT) is a rapid visual assessment framework designed to support early identification of critically ill ...