Pulmonology

Explainable AI for chest radiographs: sex-stratified fairness auditing in CNN-based pneumonia detection.

Artificial intelligence (AI) systems for chest X-ray (CXR) interpretation can achieve high standalone diagnostic accuracy, yet limited transparency raises concerns about subgroup disparities. We audited sex-stratified performance and attention patterns in CNN-based pneumonia detection using the RSNA Pneumonia Detection Challenge dataset (26,684 frontal adult CXRs). ImageNet-pretrained InceptionV3 ...

Explainable machine learning model for early prediction of ICU death in chronic heart failure with pulmonary infection.

OBJECTIVE: To develop and validate a machine learning model for predicting ICU mortality in CHF patients with pulmonary infection. METHODS: Clinical data were extracted from the MIMIC-IV database, and ICU mortality within 15 days was defined as the primary endpoint. Patients were stratified into HFrEF, HFmrEF, and HFpEF based on left ventricular ejection fraction. Six models were constructed-logis...

Bioinformatics reveals the prognostic potential of manganese metabolism-related genes in lung adenocarcinoma.

Manganese metabolism may be involved in the malignant progression of lung adenocarcinoma (LUAD). Clarifying the roles of manganese metabolism-related ...

Exosomes in cancer drug resistance: dual roles in therapy failure and emerging precision therapeutics.

Exosomes play a key role in cancer, functioning both as drivers of drug resistance and as tools for therapy. Tumor-derived exosomes facilitate interce...

DeepHeptox: An Interpretable Deep Learning Model for Multi-Endpoint Hepatotoxicity Prediction of Chemical Compounds.

Hepatotoxicity represents a major adverse outcome of chemical exposure, as the liver plays a central role in xenobiotic metabolism and detoxification....

Heart Failure sub-phenotyping and in-hospital and 28-day mortality prediction based on mean arterial pressure trajectory modeling.

BACKGROUND: Acute decompensated heart failure patients follow a broad range of clinical pathways during hospitalization. Efficient patient sub-phenoty...

Construction and validation of a nomogram prediction model for postoperative residual risk of pediatric obstructive sleep apnea based on OCTA and LASSO machine learning algorithm.

OBJECTIVE: To evaluate the value of retinal optical coherence tomography angiography (OCTA) microcirculatory parameters combined with clinical, bioche...

Bridging the Vaccine Gap: Scientific and Technological Advances for Diseases Lacking Effective Vaccines.

Despite remarkable achievements in infectious disease control, more than 20 major pathogens responsible for significant global morbidity and mortality...

Association of Histological Features of Cortical and Medullary Peritubular Capillaries With Progressive CKD.

RATIONALE & OBJECTIVE: Peritubular capillary (PTC) rarefaction occurs in chronic kidney disease (CKD), but the independent association of PTC histolog...

Reinforcement learning for treatment decision-making in sepsis: a scoping review.

This scoping review summarizes the progress of reinforcement learning (RL) in clinical decision-making for sepsis at the intersection of medicine and ...

Predicting local control of brain metastases after Gamma Knife radiosurgery: a multimodal deep learning-radiomics approach.

BACKGROUND: Accurate prediction of local control (LC) following Gamma Knife radiosurgery (GKRS) remains clinically challenging for patients with brain...

A combi-elasto ultrasound based deep learning model on liver fibrosis staging for suspected MASLD/MASH patients.

OBJECTIVES: Metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH) weakened the ...

Radiomic model with SHAP-based interpretability for predicting invasiveness of pure ground-glass nodules: a retrospective study based on high-resolution computed tomography (HRCT) volumetric datasets.

BACKGROUND: Radiomics holds promise for lung cancer diagnosis. This study developed an interpretable radiomics-clinical model to predict the invasiven...

Impact of Artificial Intelligence Assistance on Diagnosing Traumatic Pneumothorax: A Comparison of Specialist and Non-Specialist Emergency Physicians.

INTRODUCTION: Supine chest radiography is routinely used in trauma care; however, its sensitivity is limited in pneumothorax detection. Although artif...

AI analysis of elastin staining sections reveals the biological implications of cancer-related fibrosis in small-sized lung adenocarcinomas.

OBJECTIVE: Pathological "invasion" influences patient prognosis in lung adenocarcinoma (LUAD); however, diagnosis is often associated with high intero...

A Brønsted-Evans-Polanyi Relationship-Guided Machine Learning Model for Predicting H2 Activation Mechanism over Indium Oxide Surfaces across Various Oxygen Vacancies Coverages.

H2 activation mechanism governs the activity, selectivity, and stability of CO2 hydrogenation over In2O3 surfaces, which varies with the coverages of ...

Deep learning-based automated assessment of alveolar bone loss in CBCT for periodontitis.

OBJECTIVES: This study aimed to develop and validate a CBCT-based automated system for assessing radiographic alveolar bone loss (RBL) to improve the ...

Identifying severe COVID-19 risk variants modulating enhancer reporter activity in lung cells.

Common genetic variants contribute to risk for complex human diseases. However, despite thousands of associations, variants modulating disease risk an...

Editorial for "RadiolGAN: Multicenter Feasibility Study of Synthetic CT From 3D Ultra-Short Echo Time MRI for Enhanced Pulmonary Radiologic Sign Visualization".

Anchor-free temporal localization of apnea events from EEG/EOG with state-space models.

Reduced-channel polysomnography (PSG) and electroencephalography/electrooculography (EEG/EOG) signals can support obstructive sleep apnea (OSA) screen...