Pulmonology

Quality of AI chatbot-generated information on hypersensitivity pneumonitis for clinical and patient use.

BACKGROUND AND AIM: Hypersensitivity pneumonitis (HP) is a complex, immüne mediated interstitial lung disease in which accurate diagnosis and long term management require integration of clinical, radiologic, and exposure-related information. Patients increasingly use artificial intelligence (AI) based chatbots to obtain disease related information; however, the quality, readability, and patient us...

Integrative single-cell profiling and explainable AI identify monocyte-metabolic signatures as diagnostic biomarkers and candidate therapeutic targets in tuberculosis.

Tuberculosis (TB) remains a formidable global health threat, yet rapid and accurate diagnostic biomarkers capturing host immune-metabolic dysregulation remain elusive. Here, we aimed to map the TB immune microenvironment and engineer a reliable, explainable diagnostic signature targeting the macrophage-associated immune-metabolic axis. Utilizing single-cell RNA sequencing (scRNA-seq) as an explora...

Left Ventricular Thrombus in Ischemic Heart Failure: Machine-learning-based Prediction of Six-month Persistence and One-year Outcomes.

Left ventricular thrombus (LVT) in ischemic heart failure carries embolic risk; tools to anticipate persistence are limited. We studied 190 consecutiv...

A highly interpretable machine learning model for predicting lung cancer bone metastasis: uncovering the synergistic effect of routine biochemical markers.

BACKGROUND: Bone metastasis (BM) significantly impairs lung cancer prognosis and patient quality of life. Conventional imaging modalities often face l...

Leveraging Large Language Models to Integrate Clinical Knowledge and Machine Learning Predictions for Lymph Node Metastasis Prediction: Development of a Knowledge-Augmented Framework.

BACKGROUND: Lymph node metastasis (LNM) is a critical clinical indicator for determining the initial treatment strategy for patients with lung cancer....

An innovative deep learning paradigm for automated detection and accurate classification of lung nodules in magnetic resonance imaging.

Lung cancer, the predominant kind of cancer, needs considerable care, since inadequate treatment may lead to fatal outcomes. The integration of comput...

Childhood exposure to traffic-related air pollution and lung function at age 10 years: evidence of nutritional modification in a birth cohort.

BACKGROUND: Exposure to traffic-related air pollution has been associated with impaired lung function in children, yet heterogeneity in susceptibility...

Allosteric targeting of the ACE2 dimer interface by a medium-sized compound inhibits SARS-CoV-2 entry.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), enters host cells via intera...

PD-YOLO: a high-precision detection network for fine-grained lung cancer and multi-scale pulmonary nodules in CT images.

Timely and accurate Computed Tomography (CT) screening is crucial for the early clinical treatment of lung cancer and preventing the progression of ma...

A deep learning framework for histopathological analysis of pixel-level extracellular matrix variation in standard H&E-stained images.

Artificial intelligence-driven image analysis has enabled significant advances in digital pathology. However, most approaches have focused on cell or ...

A multimodal deep learning framework for precise silicosis detection on radiographic images.

Pneumoconiosis, a common occupational lung illness, arises from inhaling dust, with silicosis specifically caused by fine crystalline silica dust, lea...

Handling missing modalities in multimodal survival prediction for non-small cell lung cancer.

Accurate survival prediction in non-small cell lung cancer (NSCLC) requires integrating clinical, radiological, and histopathological data. Multimodal...

Optimizing Amiodarone Maintenance Dose to Minimize N-Desethylamiodarone Accumulation and Pulmonary Toxicity: Insights from Machine Learning and Pharmacokinetic Simulation.

BACKGROUND AND OBJECTIVE: The accumulation of N-desethylamiodarone (DEA), an active metabolite of amiodarone, is a recognized risk factor for intersti...

PCT-Anchored Machine Learning for Pre-Culture Identification of Gram-Negative Sepsis in Children: A Four-Site Study.

OBJECTIVE: Procalcitonin (PCT) has moderate accuracy for bacteremia detection but is infrequently used in pediatric emergency departments, partly due ...

Detection of rheumatoid arthritis-associated interstitial lung disease: a systematic review and meta-analysis.

BACKGROUND: Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) often has an insidious onset with few or no respiratory symptoms, so ea...

Association between dynamic digital radiography findings and post-extubation respiratory deterioration: A retrospective exploratory analysis of a prospectively collected ICU cohort.

INTRODUCTION: Dynamic Digital Radiography (DDR) is a novel bedside imaging modality that enables real-time visualization of pulmonary motion with mini...

Interpretable machine learning via symbolic classification of radiomic texture and morphological features for pediatric pneumonia detection from chest X-rays.

Explainable artificial intelligence in medical imaging is currently dominated by post-hoc tools that rationalise the decisions of otherwise opaque dee...

Artificial intelligence in the diagnosis of deep vein thrombosis: A scoping review.

Deep vein thrombosis (DVT) is the formation of thrombi in the deep venous system, most often in the lower extremities. Although usually not life-threa...

Extracellular vesicles as diagnostic and prognostic biomarkers in non-small cell lung Cancer.

INTRODUCTION: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis ...

Early prediction of severe Omicron pneumonia using a multimodal a.i. model integrating delta CT radiomics and laboratory indicators.

Early identification of patients at risk of severe pneumonia during Omicron SARS-CoV-2 infection is critical for optimizing care and allocating resour...