Pulmonology

A Hybrid Approach for Differentiating Fibrotic Hypersensitivity Pneumonitis and Idiopathic Pulmonary Fibrosis: Deep Feature Extraction and Machine Learning.

In patients over 60 years of age who are male, non-smokers, and in whom no organic antigen is identified in the history, differentiating fibrotic hypersensitivity pneumonitis (HP) from idiopathic pulmonary fibrosis (IPF) may be challenging. We aimed to evaluate the contribution of deep learning-based feature extraction and machine learning classification in differentiating these two pathologies, w...

Chest X-Ray evaluation using GPT for tube thoracostomy or conservative care in non-tension spontaneous pneumothorax.

BACKGROUND/OBJECTIVE: Spontaneous pneumothorax (SP) commonly presents to the emergency department (ED), and clinicians must rapidly decide between conservative care and tube thoracostomy. Most artificial intelligence tools focus on pneumothorax detection rather than quantitative size estimation and actionable management recommendations. We aimed to evaluate whether a vision-enabled generative pre-...

Explainable transfer learning ensemble AI model for lung ultrasound pneumothorax detection with expert benchmark.

BACKGROUND: Lung ultrasound is essential for rapid, radiation-free bedside pneumothorax diagnosis but limited by variability in human interpretation. ...

A leakage-controlled and SHAP driven machine learning framework for paediatric respiratory disease classification using Indian hospital EHR data.

Changes in computed tomography derived muscle and pulmonary tissue in patients hospitalized for COVID-19: a 12-month follow-up study.

BACKGROUND: Prolonged muscle loss and persistent pulmonary radiological manifestations have been observed among previously hospitalized COVID-19 patie...

Cross-sectional research: Application of an Artificial Intelligence-Based Pediatric Early Warning Score in the Pediatric Emergency Department.

BACKGROUND: There are a large number of pediatric emergency patients. Due to the fact that the children cannot describe their own conditions, there is...

Noninvasive Prediction of Bone Metastasis-Free Survival in Lung Adenocarcinoma Using Interpretable CT-based Deep Learning Model.

RATIONALE AND OBJECTIVES: Preoperatively identifying patients at high risk of bone metastasis (BM) remains challenging in resectable lung adenocarcino...

Cardiopulmonary exercise testing before lung resection surgery: still indicated? Evaluating predictive utility using machine learning.

RATIONALE: Despite significant advances in patient care and outcomes, criteria for cardiopulmonary exercise testing (CPET) in risk stratification guid...

Multimodal cardiovascular risk profiling using self-supervised learning of polysomnography.

STUDY OBJECTIVES: Polysomnography (PSG) provides a comprehensive assessment of brain, cardiac, and respiratory activity during sleep. While it is wide...

Scenario-based evaluation of large language models for reference accuracy in dermatology: literature retrieval on latent tuberculosis in psoriasis patients on anti-IL-17/23 therapy.

BACKGROUND: Large language models (LLMs) could accelerate clinical literature searches, but their reliability is compromised by "hallucinations" gener...

Predicting reactive graphene edge-adsorbed Pt single-atom catalyst structures for oxygen reduction via machine learning-enhanced DFT calculations.

Single-atom platinum on graphitic materials can enhance catalysis of the oxygen reduction reaction (ORR). The local atomic structure shapes catalytic ...

Tuberculosis Disease Severity Assessment Using Clinical Variables and Radiology Enabled by Artificial Intelligence.

BACKGROUND: Chest X-ray (CXR) can assess pulmonary tuberculosis (TB) severity and may guide duration of treatment. However, the optimal radiological m...

mRNASyner: An Integrative Framework for Full-Length mRNA Sequence Optimization via Multimodule Synergistic Design.

Messenger RNA (mRNA) technology holds great promise in biomedicine; however, its therapeutic efficacy relies heavily on translation efficiency and the...

Identification of hub genes and molecular networks involved in alveolar bone resorption based on bioinformatics analysis.

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 g...

A review of traditional uses, phytoconstituents, bioactivities, and therapeutic potential of Hypecoum erectum L. and Hypecoum leptocarpum Hook.f. & Thomson.

ETHNOPHARMACOLOGICAL RELEVANCE: Hypecoi Erecti Herba, derived from plants of the genus Hypecoum (Papaveraceae), includes two source species: Hypecoum ...

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-...

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-...