Pulmonology

Development and interpretation of machine learning-based prognostic models for predicting high-risk prognostic pathological components in pulmonary nodules: integrating clinical features, serum tumor marker and imaging features.

BACKGROUND: With the improvement of imaging, the screening rate of Pulmonary nodules (PNs) has further increased, but their identification of High-Risk Prognostic Pathological Components (HRPPC) is still a major challenge. In this study, we aimed to build a multi-parameter machine learning predictive model to improve the discrimination accuracy of HRPPC.

Predicting 14-day readmission in middle-aged and elderly patients with pneumonia using emergency department data: a multicentre retrospective cohort study with a survival machine learning approach.

OBJECTIVES: Unplanned pneumonia readmissions increase patient morbidity, mortality and healthcare costs. Among pneumonia patients, the middle-aged and elderly (≥45 years old) have a significantly higher risk of readmission compared with the young. Given that the 14-day readmission rate is considered a healthcare quality indicator, this study is the first to develop survival machine learning (ML) m...

Artificial intelligence-powered interpretation of lung function in interstitial lung diseases.

Fast and accurate lung cancer subtype classication and localization based on Intraoperative frozen sections of lung adenocarcinoma.

Current lung cancer diagnostic techniques primarily focus on tissue subtype classification, yet remain inadequate in distinguishing pathological progr...

Prediction of Acute Kidney Injury in Critically ill Patients with Community-Acquired Pneumonia Using Machine Learning.

BackgroundThe incidence of acute kidney injury (AKI) is increased in patients with community-acquired pneumonia (CAP), contributing to poor outcomes i...

Canadian Radiology Update.

Radiology research at Canadian institutions is advancing patient care through multidisciplinary collaboration, technological innovation, and quality i...

Identifying Clinical Research Priorities in Interventional Pulmonary: An Interventional Pulmonology Outcomes Group (IPOG) Working Group Report.

The field of Interventional Pulmonology suffers from a paucity of methodologically robust studies to inform patient care, often relying on retrospecti...

Exploring T-cell metabolism in tuberculosis: development of a diagnostic model using metabolic genes.

OBJECTIVES: The early diagnosis and immunoregulatory mechanisms of active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remain unclear, ...

Precision Medicine and Machine Learning to predict critical disease and death due to Coronavirus disease 2019 (COVID-19).

INTRODUCTION: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes Coronavirus Disease 2019 (COVID-19) and induces activation of in...

Unmet needs of patients with COPD in Germany: a retrospective, cross-sectional study.

BACKGROUND: Earlier diagnosis and treatment of COPD, particularly preventing exacerbations, are key to slowing disease progression and reducing mortal...

A machine learning model for predicting severity-adjusted in-hospital mortality in pneumonia patients.

OBJECTIVE: This study aims to develop a customized severity adjustment tool for hospital deaths in pneumonia patients considering characteristics of K...

Advances in molecular pathology and therapy of non-small cell lung cancer.

Over the past two decades, non-small cell lung cancer (NSCLC) has witnessed encouraging advancements in basic and clinical research. However, substant...

Signature gene expression model for quantitative evaluation of MASH-like liver injury in mice.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a spectrum of chronic pathologic conditions strongly associated with metabolic syn...

Melioidosis molecular diagnostics: An update.

Melioidosis, a fatal tropical disease, presents a wide array of clinical manifestations, including abscesses, pneumonia, septic shock, bacteraemia, os...

Empirical mode decomposition in clinical signal analysis: A systematic review.

This systematic review examines the transformative applications of empirical mode decomposition (EMD) in healthcare, focusing on its ability to analys...

A review: Lightweight architecture model in deep learning approach for lung disease identification.

As one of the leading causes of death worldwide, early detection of lung disease is a very important step to improve the effectiveness of treatment. B...

Machine learning-based model for acute asthma exacerbation detection using routine blood parameters.

BACKGROUND: Acute asthma exacerbations (AAEs) are a leading cause of asthma-related morbidity and mortality, especially in resource-limited settings w...

Predicting pulmonary hemodynamics in pediatric pulmonary arterial hypertension using cardiac magnetic resonance imaging and machine learning: an exploratory pilot study.

PURPOSE: Pulmonary arterial hypertension (PAH) significantly affects the pulmonary vasculature, requiring accurate estimation of mean pulmonary arteri...

Gut microbiota alterations are linked to COVID-19 severity in North African and European populations.

Although COVID-19 primarily affects the respiratory system, many patients experience gastrointestinal symptoms, suggesting a role for the gut microbio...

Targeting Mycobacterial Dormancy Survival Regulator (DosR) With Generative Artificial Intelligence and Omics Methods.

Tuberculosis, driven by Mycobacterium tuberculosis, remains a global health challenge due to the pathogen's ability to enter a dormant state, evading ...