Pulmonology

Multiview 2.5D Deep Learning Outperforms 2D and 3D Models for Preoperative Prediction of Visceral Pleural Invasion in Stage IA Lung Adenocarcinoma.

OBJECTIVE: This study evaluated the predictive performance of 2 novel 2.5-dimensional (2.5D) deep learning (DL) models for visceral pleural invasion (VPI) in clinical stage IA lung adenocarcinoma, comparing them with traditional 2D and 3D models. MATERIALS AND METHODS: A multicenter retrospective analysis included 804 patients from 2 Chinese hospitals with pathologically confirmed stage IA lung ad...

Past, present and future perspectives of traumatic brain injury.

Despite extensive research, traumatic brain injury (TBI) imposes significant mortality and morbidity burden globally. This narrative review provides a comprehensive overview of how TBI classification, surgical and critical care management, and physiological treatment goals have evolved based on recent evidence, shaping future directions for TBI care. We highlight the conceptual shift in TBI classi...

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 CT (LDCT) have been evaluated primarily using expe...

Prediction-guided clustering for sepsis phenotyping: a retrospective cohort analysis.

BACKGROUND: Sepsis is a major cause of morbidity and mortality worldwide, with its heterogeneous and dynamically evolving clinical presentation compli...

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 ill patients with gram-positive bacterial infection...

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 technologies in modern health care. However, comprehe...

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; however, only certain patients experience disease prog...

A hybrid deep learning approach integrating CNN and transformer for lung cancer classification using CT scans.

Lung cancer is an extremely fatal kind of cancer, resulting in the deaths of almost 7.6 million individuals annually around the globe. Nevertheless, a...

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 critically ill children and may arise from respiratory, c...

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 for drug repurposing, but its potential for de novo...

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 pathology despite normal alanine aminotransferase (ALT)...

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 kidney transplant recipients (KTRs). Early identifi...

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 endobronchial ultrasound (EBUS) for differentiatin...

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

Background Pulmonary rehabilitation (PR) is beneficial, yet outcome assessment remains inconsistent. A multidisciplinary D-A-CH working group reviewed...

Automated daily adaptation for breast cancer radiotherapy: benefits of deep learning-driven dose prediction workflow for CBCT-based adaptation.

Objective Daily anatomical variations can jeopardize the quality of modern radiotherapy (RT). Adaptive radiotherapy (ART) aims to address this by ...

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 function, and its measurement can guide treatment decis...