Pulmonology

Pneumonia

Latest AI and machine learning research in pneumonia for healthcare professionals.

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Community Detection in Large-Scale Complex Networks via Structural Entropy Game

Community detection is a critical task in graph theory, social network analysis, and bioinformatics, where communities are defined as clusters of densely interconnected nodes. However, detecting communities in large-scale networks with millions of nodes and billions of edges remains challenging due to the inefficiency and unreliability of existing methods. Moreover, many current approaches are l...

Deep Learning-Powered Classification of Thoracic Diseases in Chest X-Rays

Chest X-rays play a pivotal role in diagnosing respiratory diseases such as pneumonia, tuberculosis, and COVID-19, which are prevalent and present unique diagnostic challenges due to overlapping visual features and variability in image quality. Severe class imbalance and the complexity of medical images hinder automated analysis. This study leverages deep learning techniques, including transfer ...

Multimodal Sensor Dataset for Monitoring Older Adults Post Lower-Limb Fractures in Community Settings

Lower-Limb Fractures (LLF) are a major health concern for older adults, often leading to reduced mobility and prolonged recovery, potentially impair...

Community-Aware Temporal Walks: Parameter-Free Representation Learning on Continuous-Time Dynamic Graphs

Dynamic graph representation learning plays a crucial role in understanding evolving behaviors. However, existing methods often struggle with flexib...

Self-Explanation in Social AI Agents

Social AI agents interact with members of a community, thereby changing the behavior of the community. For example, in online learning, an AI social...

MedFILIP: Medical Fine-grained Language-Image Pre-training

Medical vision-language pretraining (VLP) that leverages naturally-paired medical image-report data is crucial for medical image analysis. However, ...

Enhancing Diagnostic in 3D COVID-19 Pneumonia CT-scans through Explainable Uncertainty Bayesian Quantification

Accurately classifying COVID-19 pneumonia in 3D CT scans remains a significant challenge in the field of medical image analysis. Although determinis...

AI Explainability for Power Electronics: From a Lipschitz Continuity Perspective

Lifecycle management of power converters continues to thrive with emerging artificial intelligence (AI) solutions, yet AI mathematical explainabilit...

Benchmarking Robustness of Contrastive Learning Models for Medical Image-Report Retrieval

Medical images and reports offer invaluable insights into patient health. The heterogeneity and complexity of these data hinder effective analysis. ...

Generative Medical Image Anonymization Based on Latent Code Projection and Optimization

Medical image anonymization aims to protect patient privacy by removing identifying information, while preserving the data utility to solve downstre...

VirusImmu: a novel ensemble machine learning approach for viral immunogenicity prediction.

The viruses threats provoke concerns regarding their sustained epidemic transmission, making the development of vaccines particularly important. In th...

Jan 15 2025 40323648
A Feature-Level Ensemble Model for COVID-19 Identification in CXR Images using Choquet Integral and Differential Evolution Optimization

The COVID-19 pandemic has profoundly impacted billions globally. It challenges public health and healthcare systems due to its rapid spread and seve...

Digital Twin for Smart Societies: A Catalyst for Inclusive and Accessible Healthcare

With rapid digitization and digitalization, drawing a fine line between the digital and the physical world has become nearly impossible. It has beco...

MedCT: A Clinical Terminology Graph for Generative AI Applications in Healthcare

We introduce the world's first clinical terminology for the Chinese healthcare community, namely MedCT, accompanied by a clinical foundation model M...

MedCoDi-M: A Multi-Prompt Foundation Model for Multimodal Medical Data Generation

Artificial Intelligence is revolutionizing medical practice, enhancing diagnostic accuracy and healthcare delivery. However, its adaptation in medic...

Comparison of Neural Models for X-ray Image Classification in COVID-19 Detection

This study presents a comparative analysis of methods for detecting COVID-19 infection in radiographic images. The images, sourced from publicly ava...

Activating Associative Disease-Aware Vision Token Memory for LLM-Based X-ray Report Generation

X-ray image based medical report generation achieves significant progress in recent years with the help of the large language model, however, these ...

UniProt: the Universal Protein Knowledgebase in 2025.

The aim of the UniProt Knowledgebase (UniProtKB; https://www.uniprot.org/) is to provide users with a comprehensive, high-quality and freely accessibl...

Jan 6 2025 39552041
GIT-CXR: End-to-End Transformer for Chest X-Ray Report Generation

Medical imaging is crucial for diagnosing, monitoring, and treating medical conditions. The medical reports of radiology images are the primary medi...

Deep Clustering via Community Detection

Deep clustering is an essential task in modern artificial intelligence, aiming to partition a set of data samples into a given number of homogeneous...

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