Pulmonology

PneumoScore: Risk Prediction Model for 90-Day Mortality After Lung Resection.

BACKGROUND: Lung resection is the gold-standard treatment for early stage lung cancer, but remains associated with significant mortality, highlighting the need for accurate preoperative risk prediction. This study developed a novel model to predict 90-day mortality after lung cancer resection and compared its performance with well-established models. METHODS: Data were extracted from the Brazilian...

Pediatric lung ground glass nodules: a real-world, large-scale CT cohort analysis.

BACKGROUND: Increasing detection of pediatric ground-glass nodules (GGNs) presents a clinical dilemma lacking robust evidence and guidelines. We aimed to evaluate the short-term natural course of incidental pediatric GGNs through real-world observation. METHODS: This retrospective, single-center, real-world study screened children (0-18 years) undergoing low-dose chest CT between January 1, 2010, ...

Hybrid model based on fuzzy logic and classification trees for the prediction of mortality of critical trauma patients: Pre-hospital variables from the RETRAUCI registry.

BACKGROUND: In critically injured trauma patients, tools that stratify injury severity and estimate mortality are essential. Fuzzy logic (FL) enables ...

Multi-omics identification of aging-related diagnostic genes and therapeutic targets in renal fibrosis.

BACKGROUND: Renal fibrosis is a pathological hallmark of progressive chronic kidney disease, partly driven by aging-related molecular alterations. How...

Deep Learning Morphometric Analysis on Protocol Biopsies Predicts Future Graft Function.

INTRODUCTION: The predictive value of Banff classification in protocol transplant biopsies without specific lesions is limited. Morphometry provides p...

Association between the endothelial activation and stress index and 28-day all-cause mortality in critically ill patients with chronic obstructive pulmonary disease: a retrospective cohort study and predictive model establishment based on machine learning.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) remains a major global health burden and is currently the third leading cause of death worldw...

Single-cell and spatial transcriptomic profiling of POU5F1 in Lung Adenocarcinoma: Dynamics, spatial niche, and prognosis via multi-algorithm ML.

BACKGROUND: POU5F1 (OCT4), a core regulator of pluripotency, plays an important role in tumor stemness and immune microenvironment remodeling, yet its...

Automated Delineation of Couinaud Segments on CT for Future Liver Remnant Volumetry.

Purpose To develop a deep learning model that automatically delineates the eight liver Couinaud segments and the spleen on CT for future liver remnant...

Hyperglycemia-driven metabolic memory signaling destabilizes METTL1 to trigger inflammatory hypertrophy and fibrosis in diabetic cardiomyopathy.

BACKGROUND: Diabetic cardiomyopathy (DCM) occurs in the context of coronary artery disease or pressure overload heart disease, characterized by altera...

From Fitness to Cognition: Machine-Learning Prediction of Cognitive Performance Using Physiological Parameters in Healthy Adults.

INTRODUCTION: Current cognitive tasks are not suitable for frequent monitoring of cognitive function in healthy adults. Increasing evidence suggests t...

AI and Internet of Things for Chronic Obstructive Pulmonary Disease Remote Monitoring: Systematic Review of Exacerbation Prediction and Key Physiological Variables.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide, with frequent exacerbations of COPD ...

Testing Near-Field Radio-Frequency Sensors to Predict Respiratory Distress in Patients Living With Dementia: A Pilot Feasibility and Acceptability Study.

BackgroundPeople living with dementia (PLWD) with advanced illness are prone to respiratory distress yet often cannot self-report dyspnea, delaying re...

CT quantification of interstitial lung abnormalities: a prospective comparison between supine and prone positions.

OBJECTIVE: To prospectively evaluate positional variability in quantitative CT (qCT)-derived measurements of interstitial lung abnormality (ILA) using...

Beyond NIHSS and neuroimaging: an interpretable gradient boosting model for predicting in-hospital mortality in ICU patients with acute ischemic stroke.

This study aimed to develop an interpretable machine learning model for predicting in-hospital mortality among acute ischemic stroke (AIS) patients ad...

Non-small Cell Lung Cancer in Metastatic Renal Cell Carcinoma Patients.

INTRODUCTION: Renal cell carcinoma (RCC) most commonly metastasizes to the lungs and shares risk factors with lung cancer. However, primary lung cance...

Establishing a competence model in discriminating Mycobacterium species and Mycobacterium abscessus subspecies by using surface-enhanced Raman spectroscopy.

Surface-enhanced Raman spectroscopy (SERS) is a powerful laser-based technique with high sensitivity and rapid detection. The present study aimed to e...

Use of Machine-Learning Models to Identify Clinical Features Associated With A Future Clinical Worsening Event in Patients With Pulmonary Arterial Hypertension.

Clinical worsening events are increasingly recognized as a meaningful outcome in pulmonary arterial hypertension (PAH). We applied machine-learning mo...

Publisher Correction: Machine Learning Models for Predicting Significant Liver Fibrosis in Patients with Severe Obesity and Nonalcoholic Fatty Liver Disease.

Combining generative large language models and pretrained language models for predicting acute respiratory distress syndrome progression.

Acute Respiratory Distress Syndrome (ARDS) is a life-threatening condition in which early diagnosis and timely intervention are crucial. Recent resear...

Multi-Objective Catalyst Discovery in High-Entropy Alloy Composition Space: The Role of Noble Metals on the Pareto Front for Oxygen Reduction Reaction.

Discovering new materials for electrocatalytic energy conversion reactions is a key step toward energy sustainability. However, for catalysts to be vi...