Pulmonology

Stacking machine learning model for risk stratification of acute respiratory distress syndrome after traumatic brain injury: a multicenter retrospective study.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a severe complication after traumatic brain injury (TBI), and early risk stratification may facilitate timely preventive interventions and improve clinical outcomes. METHODS: Model development used the MIMIC-IV v3.1 database with external validation in a cohort from the First Affiliated Hospital of Xinjiang Medical University. Candidate var...

YOLO-geochemical integration for real-time aeolian dust monitoring: a critical review of signatures, health risks, and policy implications.

Aeolian dust is one of the most pervasive natural air pollutants, strongly influencing atmospheric chemistry, visibility, climate feedback, and human health. This review critically evaluates the integration of geochemical fingerprinting techniques and YOLO-based deep learning frameworks for real-time aeolian dust monitoring, with the overarching objective of advancing source attribution, health ri...

Using the Machine Learning Algorithm XGBoost to Understand the Correlates of Wearing Hearing Protection in Central States' Agricultural Producers.

PURPOSE: Hearing loss is a common work-related condition. Estimates suggest that 46%-86% of agricultural workers have hearing loss. Agricultural safet...

Multimodal deep learning integration of clinical, dosiomics, and radiomics features to predict toxicity in breast cancer patients undergoing hypofractionated radiotherapy.

BACKGROUND AND PURPOSE: Radiation dermatitis (RD) and superficial soft tissue fibrosis are common toxicities among the patients with breast cancer rec...

Multidimensional proteomics and explainable AI feature selection identify cross-platform lung cancer molecular signature in blood plasma.

BACKGROUND: Lung cancer is the leading cause of cancer mortality worldwide despite the availability of low-dose computed tomography (LDCT) for screeni...

Physics-informed neural network-based simulation of pulmonary arterial hemodynamics abnormalities.

OBJECTIVES: To predict abnormal pulmonary artery hemodynamics caused by ventricular septal defect (VSD) using Physics-Informed Neural Networks (PINN) ...

Leveraging nonlinear relationships and interactions to improve 30-day pneumonia readmission machine learning models.

BACKGROUND: Research is needed to develop more accurate readmission prediction models that identify patients at the highest risk of readmission after ...

An interpretable machine learning model for preoperative risk stratification in paediatric congenital heart disease surgery: a retrospective cohort study.

BACKGROUND: Congenital heart disease (CHD), one of the most common birth defects, poses challenges to preoperative risk stratification due to its anat...

A novel deep learning network for small bowel ulcerative lesion detection and differential diagnosis on double-balloon endoscopy images.

Differentiating small bowel ulcerative diseases (SBUDs) on double-balloon endoscopy (DBE) is challenging. We aimed to develop an artificial intelligen...

Computational exploration of quercetin derivatives from Azadirachta indica leaf as threonine tyrosine kinase inhibitors for potential lung and pancreatic cancer treatment.

Lung and pancreatic adenocarcinomas account for substantial cancer-related mortality worldwide, with current therapeutic efficacy severely limited by ...

Multi-omics analysis identifies CD48 and ITIH5 as potential diagnostic biomarkers and therapeutic targets for metabolic disorders associated with obesity.

BACKGROUND: Obesity-driven metabolic disorders involve pathological remodeling of white adipose tissue (WAT), wherein fibroblasts coordinate fibrosis ...

Environmental conditions and animal hosts shape the spatial transmission risks of echinococcosis in China.

Echinococcosis poses a major public-health challenge and substantial socioeconomic burdens in pastoral regions. Yet the spatial transmission risks in ...

Machine learning versus clinical scoring systems for predicting poor wound healing after posterior surgery for thoracolumbar tuberculosis.

OBJECTIVE: Postoperative poor wound healing (PWH) is a significant complication following posterior surgery for thoracolumbar tuberculosis, leading to...

Differentiating advanced from non-advanced hepatic fibrosis: a hybrid deep learning-radiomics model leveraging synthetic contrast-enhanced CT from CycleGAN.

OBJECTIVES: This study aimed to develop and validate a hybrid deep learning-radiomics model that leveraged Cycle-consistent generative adversarial net...

Beyond scarring: a next-generation vision for pulmonary fibrosis management.

BACKGROUND: Interstitial pulmonary fibrosis remains a progressive, fatal lung disease with a median survival of approximately 4-5 years in contemporar...

Large Language Models Exhibit High Performance as Computable Phenotypes for Pediatric Asthma Exacerbation Detection in a Retrospective, Observational Study of Emergency Medical Services Encounters.

OBJECTIVES: Pediatric asthma exacerbations are a common emergent condition treated by prehospital emergency medical services (EMS). However, retrospec...

Plasma signals of lung tumor promotion for molecular cancer prevention.

Predicting lung cancer risk would enhance prevention trials. Although the Canakinumab Anti-inflammatory Thrombosis Outcome Study (CANTOS) trial demons...

A clinical support tool using artificial intelligence to diagnose pulmonary hypertension.

Development of an artificial intelligence prediction model for moderate-to-severe COPD exacerbations using continuous multiple unobtrusive sensors: protocol of a multicentre prospective observational study.

INTRODUCTION: Exacerbations, impaired health-related quality of life (HRQoL) and reduced exercise capacity increase the risk of hospitalisations and d...

Non-contact on-device detection of obstructive sleep apnea from infrared video.

Obstructive sleep apnea (OSA) affects nearly one billion people worldwide, yet most cases remain undiagnosed because standard testing requires overnig...