Artificial Intelligence Medical Compendium

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BACKGROUND: There is little research about the questions asked by people with epilepsy, and how these are answered. Information sources include standardised medical or charity websites, responses generated by artificial intelligence paradigms and inf... read more 

OBJECTIVE: To evaluate and compare the quality and readability of patient education materials (PEM) related to ankylosing spondylitis (AS) generated by four AI-based large language models (LLMs): ChatGPT-4o, ChatGPT-3.5, DeepSeek R1, and DeepSeek V3.... read more 

BACKGROUND: Clinical decision-making is shaped by healthcare provider-related factors such as experience, qualification and cognitive skills. AI-based Clinical Decision Support Systems (CDSS) promise to enhance diagnostic accuracy but may also introd... read more 

INTRODUCTION: The performance of cutting-edge generative artificial intelligence (GenAI) in guiding laypeople on how to give help in health emergencies is attracting growing attention. This study aimed to map and summarise original research evidence ... read more 

Imbalanced datasets represent a significant challenge in accurately estimating Colored Dissolved Organic Matter (CDOM) concentrations in aquatic environments. This study integrates machine learning models with synthetic data generated via classificat... read more 

PURPOSE: Clinical target volume (CTV) delineation for involved-site radiation therapy (ISRT) in Hodgkin lymphoma (HL) is time-consuming because of the need to analyze multi-timepoint positron emission tomography (PET)/computed tomography (CT) scans c... read more 

INTRODUCTION: High-resolution peripheral quantitative computed tomography (HR-pQCT) provides detailed bone microarchitecture assessments, but the interpretability of its many complex parameters remains challenging. This study aimed to develop a deep ... read more 

OBJECTIVES: To introduce a vertically integrated model between a health care service provider and technology developer as a learning accelerator to address challenges in developing and delivering artificial intelligence (AI) into health care. METHODS... read more 

Deep learning (DL) models have shown promise in predicting molecular alterations directly from hematoxylin and eosin-stained whole slide images in a variety of solid tumors, offering a rapid alternative to conventional molecular testing. However, the... read more