BACKGROUND: The advent of generative artificial intelligence has led to the emergence of multiple vision large language models (VLLMs). This study aimed to evaluate the capabilities of commonly available VLLMs, such as OpenAI's GPT-4V and Google's Ge...
OBJECTIVES: This synopsis gives insights into scientific publications from 2023 in Natural Language Processing for the biomedical domain. We present the process we followed to identify candidates for NLP's best papers and the two best papers of this ...
OBJECTIVES: Large language models (LLMs) are revolutionizing the natural language pro-cessing (NLP) landscape within healthcare, prompting the need to synthesize the latest ad-vancements and their diverse medical applications. We attempt to summarize...
OBJECTIVES: To select, present, and summarize cutting edge work in the field of Knowledge Representation and Management (KRM) published in 2022 and 2023.
OBJECTIVES: The emergence of large language models has resulted in a significant shift in informatics research and carries promise in clinical cancer care. Here we provide a narrative review of the recent use of large language models (LLMs) to suppor...
Given the scarcity of annotated data, current deep learning methods face challenges in the field of document-level chemical-disease relation extraction, making it difficult to achieve precise relation extraction capable of identifying relation types ...
Studies in health technology and informatics
40200441
This short communication presents preliminary findings on the integration of Large Language Models (LLMs) and wearable technology to generate personalized recommendations aimed at enhancing student well-being and academic performance. By analyzing di...
Studies in health technology and informatics
40200440
This short communication presents preliminary findings on the application of Large Language Models (LLMs) for sentiment analysis in educational settings. By analyzing qualitative descriptions derived from student reports, we aimed to assess students'...
OBJECTIVE: Electronic health records (EHR) are widely available to complement administrative data-based disease surveillance and healthcare performance evaluation. Defining conditions from EHR is labour-intensive and requires extensive manual labelli...
BACKGROUND: Popularized by ChatGPT, large language models (LLMs) are poised to transform the scalability of clinical natural language processing (NLP) downstream tasks such as medical question answering (MQA) and automated data extraction from clinic...