Pulmonology

Pneumonia

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

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Chest X-Ray Visual Saliency Modeling: Eye-Tracking Dataset and Saliency Prediction Model.

Radiologists' eye movements during medical image interpretation reflect their perceptual-cognitive p...

May 2025 40338721
Data Standards in Audiology: A Mixed-Methods Exploration of Community Perspectives and Implementation Considerations

Objective: The purpose of this study was to explore options for data standardisation in audiology ...

CXR-AD: Component X-ray Image Dataset for Industrial Anomaly Detection

Internal defect detection constitutes a critical process in ensuring component quality, for which ...

AOR: Anatomical Ontology-Guided Reasoning for Medical Large Multimodal Model in Chest X-Ray Interpretation

Chest X-rays (CXRs) are the most frequently performed imaging examinations in clinical settings. R...

Diagnostic Uncertainty in Pneumonia Detection using CNN MobileNetV2 and CNN from Scratch

Pneumonia Diagnosis, though it is crucial for an effective treatment, it can be hampered by uncert...

CLOG-CD: Curriculum Learning based on Oscillating Granularity of Class Decomposed Medical Image Classification

Curriculum learning strategies have been proven to be effective in various applications and have g...

Knowledge-Augmented Language Models Interpreting Structured Chest X-Ray Findings

Automated interpretation of chest X-rays (CXR) is a critical task with the potential to significan...

A Dataset for Understanding Radiologist-Artificial Intelligence Collaboration.

This dataset, Collab-CXR, provides a unique resource to study human-AI collaboration in chest X-ray ...

May 2025 40319039
Any-to-Any Vision-Language Model for Multimodal X-ray Imaging and Radiological Report Generation

Generative models have revolutionized Artificial Intelligence (AI), particularly in multimodal app...

Predicting Respiratory Disease Mortality Risk Using Open-Source AI on Chest Radiographs in an Asian Health Screening Population.

Purpose To assess the prognostic value of an open-source deep learning-based chest radiographs algor...

May 2025 40172326
IP-CRR: Information Pursuit for Interpretable Classification of Chest Radiology Reports

The development of AI-based methods for analyzing radiology reports could lead to significant adva...

SVD Based Least Squares for X-Ray Pneumonia Classification Using Deep Features

Accurate and early diagnosis of pneumonia through X-ray imaging is essential for effective treatme...

ChestX-Reasoner: Advancing Radiology Foundation Models with Reasoning through Step-by-Step Verification

Recent advances in reasoning-enhanced large language models (LLMs) and multimodal LLMs (MLLMs) hav...

AI Alignment in Medical Imaging: Unveiling Hidden Biases Through Counterfactual Analysis

Machine learning (ML) systems for medical imaging have demonstrated remarkable diagnostic capabili...

Lightweight Social Computing Tools for Undergraduate Research Community Building

Many barriers exist when new members join a research community, including impostor syndrome. These...

Meta-Entity Driven Triplet Mining for Aligning Medical Vision-Language Models

Diagnostic imaging relies on interpreting both images and radiology reports, but the growing data ...

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 issu...

Leveraging LLMs for Multimodal Retrieval-Augmented Radiology Report Generation via Key Phrase Extraction

Automated radiology report generation (RRG) holds potential to reduce radiologists' workload, espe...

Generative Large Language Models Trained for Detecting Errors in Radiology Reports

In this retrospective study, a dataset was constructed with two parts. The first part included 1,6...

Task as Context Prompting for Accurate Medical Symptom Coding Using Large Language Models

Accurate medical symptom coding from unstructured clinical text, such as vaccine safety reports, i...

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