Pulmonology

Discrimination between Mycobacterium tuberculosis and Mycobacterium bovis using Fourier transform infrared spectroscopy.

Zoonotic tuberculosis (TB) caused by Mycobacterium bovis (Mbo) is a neglected disease that hinders efforts to eradicate human tuberculosis. Developing a rapid, high-throughput diagnostic test to distinguish Mbo from Mycobacterium tuberculosis (Mtb) isolates could enhance global zoonotic TB diagnostics and surveillance. This study aimed to evaluate the ability of Fourier Transform Infrared Spectros...

Personalized sepsis mortality prediction: An interpretable machine learning nomogram.

PURPOSE: Sepsis remains a major cause of mortality in ICU patients, requiring accurate prognostic tools for optimal management. This study aimed to develop and validate an interpretable machine learning-based nomogram for predicting in-hospital mortality in sepsis patients to guide clinical decision-making. METHODS: This retrospective cohort study included 407 adult sepsis patients from ICU admiss...

Compound Dry-Hot Events Intensify Widespread Lake Deoxygenation in China.

Lake deoxygenation, driven by climatic warming and anthropogenic influences, threatens aquatic ecosystems. As climate change intensifies, compound dry...

A multi-level segmentation-guided diffusion model for streak artifact reduction in routine non-contrast chest CT.

Streak artifacts in non-contrast computed tomography (NCCT) can obscure anatomical details and even confuse radiologic signs. Existing methods for art...

Feasibility of BMI-based sub-milliSievert low-dose CT in individualized detection of lung nodules.

OBJECTIVES: To evaluate the performance of a body mass index (BMI)-based sub-milliSievert low-dose CT (LDCT) protocol with multiple reconstruction alg...

Clinically applicable deep learning model for segmentation of the mandibular bone and inferior alveolar canal in CBCT cross-sectional images.

Association of cardiovascular-kidney-metabolic syndrome stages with MASLD prevalence and liver fibrosis severity: evidence from traditional and machine learning approaches.

INTRODUCTION: Cardiovascular-Kidney-Metabolic (CKM) syndrome reflects the convergence of cardiovascular, renal, and metabolic disorders. Metabolic dys...

Predicting neoadjuvant immunotherapy efficacy with machine learning models in non-small cell lung cancer: A systematic review and meta analysis.

BACKGROUND: The response of resectable non-small cell lung cancer (NSCLC) to neoadjuvant immunotherapy is heterogeneous. Machine learning can integrat...

Electrochemical biosensors for Calreticulin in lung Cancer.

Electrochemical biosensors represent an advanced and novel technology for the sensitive and specific detection of clinically relevant biomarkers. Of t...

A machine learning model to identify pulmonary embolism in patients admitted to intensive care.

BACKGROUND: Pulmonary embolism (PE) is a leading cause of preventable death, yet statistical prediction models have shown inconsistent validity. Our p...

Machine learning and bioinformatics-based identification of mitophagy-related diagnostic biomarkers in bronchiolitis obliterans.

This study aimed to explore the molecular mechanisms associated with mitophagy in BO and identified mitophagy-associated BO diagnostic genes. Using Ge...

Research on the Prediction of Coal Workers' Pneumoconiosis Based on Easily Detectable Clinical Data: Machine Learning Model Development and Validation Study.

BACKGROUND: Coal workers' pneumoconiosis (CWP) is the most prevalent occupational disease that causes irreversible lung damage. Early prediction of CW...

Surface Tracking-Assisted Multi-Cycle 4D MRI Motion Modeling for Lung Radiotherapy: A Preliminary Validation Study.

To validate a respiratory motion model that uses real-time electromagnetic (EM) surface tracking acquired concurrently with time-resolved multi-cycle ...

MS-HIENet: multi-scale hybrid implicit-explicit registration network.

Medical image registration serves as a cornerstone for precision diagnosis and treatment, particularly for dynamic organs like the lungs, where high d...

A lightweight residual dilated temporal transformer block for ECG classification on edge devices.

Wearable devices play a crucial role in healthcare by enabling continuous monitoring of vital physiological signals such as ECG, heart rate, respirati...

A hybrid LSTM-GRU framework for lung cancer classification using GWO-WOA algorithm for hyperparameter tuning and BPSO for feature selection.

Early identification of lung cancer using questionnaire-based data offers a low-cost, non-invasive pathway to assist clinical decision-making. However...

Development of Radiomics Models to Predict Progression-Free Survival and Early Polymetastatic Progression in Patients With Lung Oligometastases Treated on the Single-Arm Phase II Stereotactic Ablative Radiotherapy-5 Trial.

AIMS: Despite the increasing use of stereotactic ablative radiotherapy (SABR) for oligometastatic cancer, at present, accurate models to predict the t...

A deep learning and morphometric hybrid model for automated quantification of kidney interstitial fibrosis in trichrome-stained whole-slide image.

BACKGROUND: Interstitial fibrosis (IF) is the strongest predictor of chronic kidney disease progression. Visual estimation of IF from trichrome (TRI)-...

Artificial intelligence-enhanced ECG score for perioperative risk assessment in non-cardiac surgery.

AIMS: The role of electrocardiography (ECG) has been limited in the preoperative risk evaluation in noncardiac surgery due to its low prognostic value...

Street-level ambient fine particulate matter and tuberculosis: A machine learning and Bayesian spatiotemporal analysis.

Tuberculosis (TB) remains a leading cause of death from infectious diseases globally, yet evidence linking short-term ambient fine particulate matter ...