Pulmonology

Respiratory microbiota maturation enables machine learning based age prediction in chickens.

Artificial Intelligence-Assisted Lung Nodule Evaluation on Low-Dose Chest CT in Asymptomatic Individuals: A Prospective Randomized Controlled Trial.

Background: The impact of artificial intelligence (AI) tools for lung nodule evaluation on low-dose ...

Development and validation of an artificial intelligence-based model for predicting teicoplanin plasma concentrations in intensive care unit patients with pulmonary infections: a retrospective study.

INTRODUCTION: Teicoplanin is widely used to treat pulmonary infections, particularly in critically i...

Approval of AI-Based Medical Devices in China From 2020 to 2025: Retrospective Analysis.

BACKGROUND: Artificial intelligence-based medical devices (AIMDs) have emerged as transformative tec...

Machine Learning Predicts ICU In-Hospital Mortality in Ards Patients Aged 80 and Above: A Multinational Multicenter Retrospective Study.

BACKGROUND: The present study aims to develop and validate an interpretable machine learning (ML) mo...

Predicting progression of Mycobacterium avium complex pulmonary disease with treatment using explainable artificial intelligence techniques.

OBJECTIVES: The incidence of nontuberculous mycobacterial pulmonary disease (NTM-PD) is rising; howe...

Machine learning prediction of tuberculosis mortality: a comparative analysis of random survival forest and cox regression models.

Signs and symptoms indicating the transition to the palliative phase in patients with COPD and heart failure in primary healthcare: a mixed-methods study.

DeePedIMV: Deep learning model for early prediction of invasive mechanical ventilation in critically ill children.

BACKGROUND: Acute deterioration requiring invasive mechanical ventilation (IMV) is common in critica...

Deep-learning-based de novo discovery and design of therapeutics that reverse disease-associated transcriptional phenotypes.

Identifying drugs that reverse disease-associated transcriptomic features has been widely explored f...

Noninvasive Detection of Occult yet Significant Liver Pathology in Alanine Aminotransferase-Normal Chronic Hepatitis B: A Multicenter Study.

BACKGROUND: Individuals with chronic hepatitis B (CHB) may harbor occult yet significant liver patho...

Identification of key influencing factors of health information literacy in COPD patients: a cross-sectional study using a random forest model.

Development and Validation of a Machine Learning-Based Nomogram for Predicting Severe Pneumocystis jirovecii Pneumonia in Kidney Transplant Recipients.

BACKGROUND Pneumocystis jirovecii pneumonia (PJP) is a life-threatening opportunistic infection in k...

Value of Endobronchial Ultrasound-Derived Radiomics in Differentiating Pulmonary Sarcoidosis from Mediastinal Lymph Node Tuberculosis.

INTRODUCTION: To explore the feasibility of an ultrasound radiomics machine learning model based on ...

The Montafon proposal: New insights and emerging concepts in pulmonary rehabilitation.

Background Pulmonary rehabilitation (PR) is beneficial, yet outcome assessment remains inconsistent....

Comparison of Left Ventricular Ejection Fraction Among 18F-FDG Dual-Gated PET/CT, Single-Gated PET/MRI, and Cardiac MRI.

Left ventricular ejection fraction (LVEF) is a critical parameter in the evaluation of cardiac funct...

A comprehensive analysis of retrieving optically inactive indicators from multi-level remote sensing product(s) in Irish waters using data science techniques.

The present research was carried out to retrieve dissolved oxygen (DOX) using the Copernicus Marine ...

Plasma proteomic profiling with machine learning identifies immunometabolic perturbations associated with smoking and smoking cessation.

Cigarette smoking is the leading modifiable risk factor for chronic obstructive pulmonary disease (C...

Biosphere expansion drives Earth's secular oxygenation while tectonics modulate oxygen variability revealed by machine learning.

The rise of atmospheric oxygen fundamentally transformed Earth's surface environment and enabled the...

Interpretable Multi-Modality Consensus QSAR Framework: Integrating Machine and Deep Learning for Enhanced Multi-Endpoint Toxicity Assessment.

Accurate toxicity assessment is essential for chemical safety, but experimental testing is costly, s...

Combining computed tomography radiomics and clinical features to predict lymph node metastasis in patients with lung cancer.

BACKGROUND: Accurate preoperative assessment of lymph node metastasis (LNM) is crucial for treatment...