Pulmonology

Hybrid Approach Combining Ultrasound and Blood Test Analysis with a Voting Classifier for Accurate Liver Fibrosis and Cirrhosis Assessment

Liver cirrhosis is an insidious condition involving the substitution of normal liver tissue with fibrous scar tissue and causing major health complications. The conventional method of diagnosis using liver biopsy is invasive and, therefore, inconvenient for use in regular screening. In this paper,we present a hybrid model that combines machine learning techniques with clinical data and ultrasoun...

Machine learning algorithms reveal gut microbiota signatures associated with chronic hepatitis B-related hepatic fibrosis.

BACKGROUND: Hepatic fibrosis (HF) represents a pivotal stage in the progression and potential reversal of cirrhosis, underscoring the importance of early identification and therapeutic intervention to modulate disease trajectory.

MERA: Multimodal and Multiscale Self-Explanatory Model with Considerably Reduced Annotation for Lung Nodule Diagnosis

Lung cancer, a leading cause of cancer-related deaths globally, emphasises the importance of early detection for better patient outcomes. Pulmonary ...

Assessing the Utility of Audio Foundation Models for Heart and Respiratory Sound Analysis

Pre-trained deep learning models, known as foundation models, have become essential building blocks in machine learning domains such as natural lang...

[Serum proteomics and machine learning unveil new diagnostic biomarkers for tuberculosis in adolescents and young adults].

Adolescents and young adults (AYAs) are one of the major populations susceptible to tuberculosis. However, little is known about the unique characteri...

Severity Classification of Chronic Obstructive Pulmonary Disease in Intensive Care Units: A Semi-Supervised Approach Using MIMIC-III Dataset

Chronic obstructive pulmonary disease (COPD) represents a significant global health burden, where precise severity assessment is particularly critic...

Waveform-Logmel Audio Neural Networks for Respiratory Sound Classification

Auscultatory analysis using an electronic stethoscope has attracted increasing attention in the clinical diagnosis of respiratory diseases. Recently...

Anatomy-constrained modelling of image-derived input functions in dynamic PET using multi-organ segmentation

Accurate kinetic analysis of [$^{18}$F]FDG distribution in dynamic positron emission tomography (PET) requires anatomically constrained modelling of...

Evaluating Vision Language Models (VLMs) for Radiology: A Comprehensive Analysis

Foundation models, trained on vast amounts of data using self-supervised techniques, have emerged as a promising frontier for advancing artificial i...

MSAD-Net: Multiscale and Spatial Attention-based Dense Network for Lung Cancer Classification

Lung cancer, a severe form of malignant tumor that originates in the tissues of the lungs, can be fatal if not detected in its early stages. It rank...

Comparative Evaluation of Radiomics and Deep Learning Models for Disease Detection in Chest Radiography

The application of artificial intelligence (AI) in medical imaging has revolutionized diagnostic practices, enabling advanced analysis and interpret...

Uncertainty-Guided Coarse-to-Fine Tumor Segmentation with Anatomy-Aware Post-Processing

Reliable tumor segmentation in thoracic computed tomography (CT) remains challenging due to boundary ambiguity, class imbalance, and anatomical vari...

Respiratory Inhaler Sound Event Classification Using Self-Supervised Learning

Asthma is a chronic respiratory condition that affects millions of people worldwide. While this condition can be managed by administering controller...

FHBench: Towards Efficient and Personalized Federated Learning for Multimodal Healthcare

Federated Learning (FL) has emerged as an effective solution for multi-institutional collaborations without sharing patient data, offering a range o...

Accurate Diagnosis of Respiratory Viruses Using an Explainable Machine Learning with Mid-Infrared Biomolecular Fingerprinting of Nasopharyngeal Secretions

Accurate identification of respiratory viruses (RVs) is critical for outbreak control and public health. This study presents a diagnostic system tha...

Deconfounded Reasoning for Multimodal Fake News Detection via Causal Intervention

The rapid growth of social media has led to the widespread dissemination of fake news across multiple content forms, including text, images, audio, ...

Exploring Modality Disruption in Multimodal Fake News Detection

The rapid growth of social media has led to the widespread dissemination of fake news across multiple content forms, including text, images, audio, ...

Boosting multi-demographic federated learning for chest x-ray analysis using general-purpose self-supervised representations

Reliable artificial intelligence (AI) models for medical image analysis often depend on large and diverse labeled datasets. Federated learning (FL) ...

The Efficacy of Semantics-Preserving Transformations in Self-Supervised Learning for Medical Ultrasound

Data augmentation is a central component of joint embedding self-supervised learning (SSL). Approaches that work for natural images may not always b...

Novel Pooling-based VGG-Lite for Pneumonia and Covid-19 Detection from Imbalanced Chest X-Ray Datasets

This paper proposes a novel pooling-based VGG-Lite model in order to mitigate class imbalance issues in Chest X-Ray (CXR) datasets. Automatic Pneumo...