Humans face various diseases that are mainly caused by environmental conditions and living habits. These diseases exhibit several symptoms and can share a relationship based on their symptoms. The identification and interpretation of these groups of ...
BACKGROUND: Retrieval-augmented generation (RAG) is increasingly used to improve large language models in the medical and nursing domains. However, a comprehensive understanding of its specific architecture and applications in medical and nursing rea...
BACKGROUND: ChatGPT has demonstrated strong performance in the complex, full clinical workflow. In recent years, several large language models (LLMs) from China have been introduced; however, their performance in such intricate tasks has yet to be th...
BACKGROUND: Accurate staging of esophageal cancer is crucial for determining prognosis and guiding treatment strategies, but manual interpretation of radiology reports by clinicians is prone to variability and limited accuracy, resulting in reduced s...
OBJECTIVES: Antimicrobial resistance is a critical public health threat. Large language models (LLMs) show great capability for providing health information. This study evaluates the effectiveness of LLMs in providing information on antibiotic use an...
BACKGROUND: In the digital age, social media has become a crucial platform for public discourse on diverse health-related topics, including vaccines. Efficient sentiment analysis and hesitancy detection are essential for understanding public opinions...
BACKGROUND: As clinical trials scale up and grow more complex, researchers are facing mounting challenges, including inefficient participant recruitment, complex data management, and limited risk monitoring. These issues not only increase the workloa...
INTRODUCTION: Community health workers (CHWs) are critical to healthcare delivery in low-resource settings but often lack formal clinical training, limiting their decision-making. Large language models (LLMs) could provide real-time, context-specific...
BACKGROUND: Large language model (LLM)-based artificial intelligence (AI) coaches show promise for personalized exercise and health interventions. However, the unique demands of ensuring safety and real-time, multimodal personalized feedback have cre...
. Decoding attempted speech from neural activity offers a promising avenue for restoring communication abilities in individuals with speech impairments. Previous studies have focused on mapping neural activity to text using phonemes as the intermedia...
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