Pulmonology

Current understanding and future directions in severe asthma through artificial intelligence-integrated multi-omic approaches.

Severe asthma remains a challenging, heterogeneous condition, despite significant advances in therapeutic strategies. A subset of patients continues to experience poor control, frequent exacerbations and a high burden of disease. The advent of multi-omic technologies, including genomics, transcriptomics, proteomics and metabolomics, has opened new avenues for understanding the molecular underpinni...

Lessons from the first U.S. school districts with real-time indoor environmental quality (IEQ) sensors in classrooms: benefits, barriers and opportunities.

With aging buildings, rising temperatures, and limited budgets, school districts in the United States need effective strategies to address classroom environmental issues, secure funding for upgrades, and develop climate resilience plans. Collecting real-time indoor environmental quality (IEQ) data in classrooms can support these goals, yet few districts have adopted comprehensive school environmen...

Multi-dimensional risk prediction and genetic architecture of aspiration pneumonia: a population-based analysis.

BACKGROUND: Aspiration pneumonia represents a significant but understudied cause of morbidity and mortality, particularly among aging populations with...

Integrative analysis and experimental validation of dioxin-interacting genes reveal diagnostic and prognostic biomarkers in lung adenocarcinoma.

Dioxins are persistent environmental pollutants and key components of the human exposome with established carcinogenic potential. As airborne toxicant...

Local control and dose selection for lung cancer brain metastases treated with radiosurgery: an artificial intelligence model.

Clinical and radiological outcomes after Stereotactic radiosurgery (SRS) for lung cancer brain metastases are heterogeneous, and prescription dose sel...

Semi-automatic individual tooth segmentation from CBCT images using anatomy-guided deep neural networks and watershed transform.

Individual tooth segmentation in cone beam computed tomography (CBCT) scan plays a crucial role in quantitatively analyzing oral diseases. However, th...

Multicentre prospective cohort study to develop and validate a machine learning-based model for predicting 6-month all-cause mortality in elderly patients with advanced chronic obstructive pulmonary disease in China: study protocol.

INTRODUCTION: Chronic obstructive pulmonary disease (COPD) has an unpredictable clinical course, causing difficulties in short-term mortality predicti...

Artificial Intelligence Tools for Diagnosing the Relationship Between the Inferior Alveolar Nerve and the Third Molar: A Systematic Review.

OBJECTIVE: To evaluate the diagnostic capability of artificial intelligence (AI) compared to human radiographic interpretation in assessing the relati...

Integrated transcriptomic analysis identifies liver aging-driven fibrosis signatures and reveals therapeutic strategies based on medicine-food homology.

Despite its strong regenerative capacity, liver aging paradoxically increases susceptibility to fibrosis and metabolic dysfunction-associated steatoti...

Unveiling gene modules at Atlas scale through hierarchical clustering of single-cell data.

A major challenge in single-cell RNA sequencing (scRNA-seq) analysis is recovering biologically meaningful cell ontology trees and conserved gene modu...

A visual analysis of the research dynamics of biomarkers for lung cancer screening.

BACKGROUND: Non-invasive biomarkers offer potential to improve risk stratification and early diagnosis of lung cancer, complementing low-dose computed...

Emerging applications of traditional and generative artificial intelligence in Liver Transplantation.

Artificial intelligence (AI) has emerged as a transformative force in liver transplantation (LT), spanning patient selection, donor-recipient matching...

Targeting Tau-Mitochondrial Crosstalk in Alzheimer's Disease: Integrative Multi-Omics and Artificial Intelligence-Driven Tools for the Development of Disease-Modifying Therapeutics.

Alzheimer's disease (AD) is a progressive neurodegenerative illness marked by cognitive impairment, synaptic dysfunction and neuronal death. Tau prote...

Methods for determining indications for antibiotic prescriptions to facilitate antimicrobial stewardship: a scoping review.

BACKGROUND: Effective antimicrobial stewardship (AMS) requires accurate information on the reason for prescribing antimicrobials. To design targeted i...

A review of deep learning-based multimodal data integration of lung cancer.

This is a narrative review that provides a perspective on the recent advances in deep learning (DL)-driven multimodal data integration for lung cancer...

Optimizing Renal Fibrosis Assessment in Patients with Chronic Kidney Disease: Feature and Decision-Level Fusion in Machine Learning Using Clinical and Ultrasound Information.

PURPOSE: Machine learning has been extensively applied in nephrology. This study aims to evaluate and compare the effectiveness of various information...

High-fidelity super-resolution microscopy datasets spanning multispectral to hyperspectral domains via diffractive optics.

Paired datasets are critical for advancing data-driven microscopy but remain scarce for spectral imaging. Here, we present a comprehensive super-resol...

Integration of single-cell RNA-sequencing and machine learning identifies GRN and FCER1G as potential peroxisomal targets in influenza pathogenesis.

BACKGROUND: Influenza, an acute respiratory infection caused by influenza viruses, imposes a significant burden on the healthcare system. Peroxisomes ...

Development of a deep-learning model for classification of intensivists' extubation decisions using ventilator graphic monitor images: a prospective observational study.

BACKGROUND: Timely extubation requires advanced expertise and extensive clinical experience; however, intensive care specialists are scarce globally, ...

MicroRNAs in endometriosis: bioinformatics resources, machine learning strategies, and multi-omics perspectives.

BACKGROUND: Endometriosis is a heterogeneous gynecological disorder characterized by chronic pain, infertility, and substantial impairment of quality ...