Pulmonology

Serum Exosomal Multi-Omic Signatures Stratify Glucose Tolerance in Cystic Fibrosis and Reveal Partial Therapeutic Reprogramming by CFTR Modulators

Cystic fibrosis-related diabetes (CFRD) affects up to 60% of adults with CF and contributes to poorer clinical outcomes, including accelerated lung decline and increased mortality. CFRD is often diagnosed late, with limited mechanistic insight and few tools for early detection. We profiled serum-derived exosomes from 186 individuals, 173 with CF, across two independent cohorts (Australia and Denma...

The impacts of artificial intelligence on the workload of diagnostic radiology services: A rapid review and stakeholder contextualisation

Advancements in imaging technology, alongside increasing longevity and co-morbidities, have led to heightened demand for diagnostic radiology services. However, there is a shortfall in radiology and radiography staff to acquire, read and report on such imaging examinations. Artificial intelligence (AI) has been identified, notably by AI developers, as a potential solution to impact positively the ...

Large Language Models Improve Coding Accuracy and Reimbursement in a Neonatal Intensive Care Unit

Diagnosis coding is essential for clinical care, research validity, and hospital reimbursement. In neonatal settings, manual coding is frequently erro...

A conversational artificial intelligence based web application for medical conversations: a prototype for a chatbot

Artificial Intelligence (AI) has evolved through various trends, with different subfields gaining prominence over time. Currently, Conversational Arti...

Explainable machine learning for post PKR surgery follow-up

Photorefractive Keratectomy (PRK) is a widely used laser-assisted refractive surgical technique. In some cases, it leads to temporary subepithelial in...

Deep learning predicts cardiac output from seismocardiographic signals in heart failure

Determination of cardiac output (CO) is essential to the clinical management of cardiovascular compromise. However, the invasiveness, procedural risks...

A clinically relevant morpho-molecular classification of lung neuroendocrine tumours

Lung neuroendocrine tumours (NETs, also known as carcinoids) are rapidly rising in incidence worldwide but have unknown aetiology and limited therapeu...

Multimodal Deep Learning for ARDS Detection

Poor outcomes in acute respiratory distress syndrome (ARDS) can be alleviated with tools that support early diagnosis. Current machine learning method...

Benign-Malignant Classification of Pulmonary Nodules in CT Images Based on Fractal Spectrum Analysis

This study reveals that pulmonary nodules exhibit distinct multifractal characteristics, with malignant nodules demonstrating significantly higher fra...

Revolutionizing Lung Cancer Detection: Evaluating AI Models for VOC Analysis and Unveiling Key Exhaled Biomarkers

Volatile Organic Compounds (VOCs) are organic chemicals that readily vaporize at room temperature and are emitted from diverse sources, including pain...

Light Convolutional Neural Network to Detect Chronic Obstructive Pulmonary Disease (COPDxNet): A Multicenter Model Development and External Validation Study

Approximately 70% of adults with chronic obstructive pulmonary disease (COPD) remain undiagnosed. Opportunistic screening using chest computed tomogra...

Predicting Tuberculosis Incidence in Adult HIV Patients on ART in Debre Markos, Ethiopia: A Machine Learning Approach

Tuberculosis (TB) is the commonest comorbidity among individuals with HIV/AIDS, especially in low- and middle-income nations such as Ethiopia. Early d...

Performance of Universal and Stratified Computer-Aided Detection Thresholds for Chest X-Ray-Based Tuberculosis Screening: A Cross-Sectional Diagnostic Accuracy Study

Computer-aided detection (CAD) software analyzes chest X-rays for features suggestive of tuberculosis (TB) and provides a numeric abnormality score. H...

Interpretable machine learning coupled to spatial transcriptomics unveils mechanisms of macrophage-driven fibroblast activation in ischemic cardiomyopathy

Myocardial infarction (MI) often leads to ischemic cardiomyopathy, which is characterized by extensive cardiac remodeling and pathological fibrosis ac...

Convolutional neural networks quantify antibiotic resistance in Mycobacterium tuberculosis with diagnostic grade accuracy and predict treatment response

There is considerable interest in training machine learning (ML) models on genomic data that achieve clinical grade diagnostic accuracy. Many successf...

Identifying Key Predictive Features for Opioid Use Disorder Using Machine Learning

Opioid Use Disorder (OUD) continues to pose a pressing public health challenge across the United States, highlighting the critical need for early and ...

A hybrid computer vision model to predict lung cancer in diverse populations

Disparities of lung cancer incidence exist in Black populations and screening criteria underserve Black populations due to disparately elevated risk i...

Spirometry parameter prediction using Acoustic characteristics of Cough

Spirometry evaluates lung function by measuring airflow post-maximal inspiration, using parameters like FEV1, FVC, and the FEV1/FVC ratio for respirat...

The Development and Evaluation of AI-based Tuberculosis Screening with a Digital Stethoscope used to Capture Lung Sounds. A Case-Control Study

Tuberculosis (TB) remains a leading global cause of preventable death, with 10.8 million cases and 1.3 million deaths reported in 2023. Current method...

Predicting overall survival of NSCLC patients with clinical, radiomics and deep learning features

Accurate estimation of Overall Survival (OS) in Non-Small Cell Lung Cancer (NSCLC) patients provides critical insights for treatment planning. While p...