Pneumonia

A Critical Review of Predominant Bias in Neural Networks

Bias issues of neural networks garner significant attention along with its promising advancement. Among various bias issues, mitigating two predominant biases is crucial in advancing fair and trustworthy AI: (1) ensuring neural networks yields even performance across demographic groups, and (2) ensuring algorithmic decision-making does not rely on protected attributes. However, upon the investig...

ProMRVL-CAD: Proactive Dialogue System with Multi-Round Vision-Language Interactions for Computer-Aided Diagnosis

Recent advancements in large language models (LLMs) have demonstrated extraordinary comprehension capabilities with remarkable breakthroughs on various vision-language tasks. However, the application of LLMs in generating reliable medical diagnostic reports remains in the early stages. Currently, medical LLMs typically feature a passive interaction model where doctors respond to patient queries ...

Development of a pressure ulcer stage determination system for community healthcare providers using a vision transformer deep learning model.

This study reports the first steps toward establishing a computer vision system to help caregivers of bedridden patients detect pressure ulcers (PUs) ...

ExoMiner++: Enhanced Transit Classification and a New Vetting Catalog for 2-Minute TESS Data

We present ExoMiner++, an enhanced deep learning model that builds on the success of ExoMiner to improve transit signal classification in 2-minute T...

Cancer Vaccine Adjuvant Name Recognition from Biomedical Literature using Large Language Models

Motivation: An adjuvant is a chemical incorporated into vaccines that enhances their efficacy by improving the immune response. Identifying adjuvant...

The Devil is in the Prompts: De-Identification Traces Enhance Memorization Risks in Synthetic Chest X-Ray Generation

Generative models, particularly text-to-image (T2I) diffusion models, play a crucial role in medical image analysis. However, these models are prone...

Enhancing Pneumonia Diagnosis and Severity Assessment through Deep Learning: A Comprehensive Approach Integrating CNN Classification and Infection Segmentation

Lung disease poses a substantial global health challenge, with pneumonia being a prevalent concern. This research focuses on leveraging deep learnin...

The Human Labour of Data Work: Capturing Cultural Diversity through World Wide Dishes

This paper provides guidance for building and maintaining infrastructure for participatory AI efforts by sharing reflections on building World Wide ...

A Generative Framework for Bidirectional Image-Report Understanding in Chest Radiography

The rapid advancements in large language models (LLMs) have unlocked their potential for multimodal tasks, where text and visual data are processed ...

AI-Driven Electronic Health Records System for Enhancing Patient Data Management and Diagnostic Support in Egypt

Digital healthcare infrastructure is crucial for global medical service delivery. Egypt faces EHR adoption barriers: only 314 hospitals had such sys...

Chest X-ray Foundation Model with Global and Local Representations Integration

Chest X-ray (CXR) is the most frequently ordered imaging test, supporting diverse clinical tasks from thoracic disease detection to postoperative mo...

Clinically-Inspired Hierarchical Multi-Label Classification of Chest X-rays with a Penalty-Based Loss Function

In this work, we present a novel approach to multi-label chest X-ray (CXR) image classification that enhances clinical interpretability while mainta...

RadVLM: A Multitask Conversational Vision-Language Model for Radiology

The widespread use of chest X-rays (CXRs), coupled with a shortage of radiologists, has driven growing interest in automated CXR analysis and AI-ass...

CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models

Deep learning models for medical image classification tasks are becoming widely implemented in AI-assisted diagnostic tools, aiming to enhance diagn...

MedRAX: Medical Reasoning Agent for Chest X-ray

Chest X-rays (CXRs) play an integral role in driving critical decisions in disease management and patient care. While recent innovations have led to...

Machine Learning Model Predictors of Intrapleural Tissue Plasminogen Activator and DNase Failure in Pleural Infection: A Multicenter Study.

Intrapleural enzyme therapy (IET) with tissue plasminogen activator (tPA) and DNase has been shown to reduce the need for surgical intervention for c...

Sleep efficiency in community-dwelling persons living with dementia: exploratory analysis using machine learning.

STUDY OBJECTIVES: Sleep disturbances lead to negative health outcomes and caregiver burden, particularly in community settings. This study aimed to in...

VICCA: Visual Interpretation and Comprehension of Chest X-ray Anomalies in Generated Report Without Human Feedback

As artificial intelligence (AI) becomes increasingly central to healthcare, the demand for explainable and trustworthy models is paramount. Current ...

Atla Selene Mini: A General Purpose Evaluation Model

We introduce Atla Selene Mini, a state-of-the-art small language model-as-a-judge (SLMJ). Selene Mini is a general-purpose evaluator that outperform...

Lightweight Weighted Average Ensemble Model for Pneumonia Detection in Chest X-Ray Images

Pneumonia is a leading cause of illness and death in children, underscoring the need for early and accurate detection. In this study, we propose a n...