Journal of the American Medical Informatics Association : JAMIA
Sep 1, 2024
OBJECTIVES: Generative large language models (LLMs) are a subset of transformers-based neural network architecture models. LLMs have successfully leveraged a combination of an increased number of parameters, improvements in computational efficiency, ...
Journal of the American Medical Informatics Association : JAMIA
Sep 1, 2024
OBJECTIVE: To solve major clinical natural language processing (NLP) tasks using a unified text-to-text learning architecture based on a generative large language model (LLM) via prompt tuning.
Journal of the American Medical Informatics Association : JAMIA
Sep 1, 2024
OBJECTIVE: Recently, large language models (LLMs) have showcased remarkable capabilities in natural language understanding. While demonstrating proficiency in everyday conversations and question-answering (QA) situations, these models frequently stru...
Journal of the American Medical Informatics Association : JAMIA
Sep 1, 2024
OBJECTIVES: The rapid expansion of biomedical literature necessitates automated techniques to discern relationships between biomedical concepts from extensive free text. Such techniques facilitate the development of detailed knowledge bases and highl...
Journal of the American Medical Informatics Association : JAMIA
Sep 1, 2024
OBJECTIVES: This comparative analysis aims to assess the efficacy of encoder Language Models for clinical tasks in the Spanish language. The primary goal is to identify the most effective resources within this context.
Journal of the American Medical Informatics Association : JAMIA
Sep 1, 2024
OBJECTIVE: Most existing fine-tuned biomedical large language models (LLMs) focus on enhancing performance in monolingual biomedical question answering and conversation tasks. To investigate the effectiveness of the fine-tuned LLMs on diverse biomedi...
Journal of the American Medical Informatics Association : JAMIA
Sep 1, 2024
OBJECTIVE: In this study, we investigate the potential of large language models (LLMs) to complement biomedical knowledge graphs in the training of semantic models for the biomedical and clinical domains.
Journal of the American Medical Informatics Association : JAMIA
Sep 1, 2024
OBJECTIVE: The use of electronic health records (EHRs) for clinical risk prediction is on the rise. However, in many practical settings, the limited availability of task-specific EHR data can restrict the application of standard machine learning pipe...
Journal of the American Medical Informatics Association : JAMIA
Sep 1, 2024
OBJECTIVE: Information retrieval (IR, also known as search) systems are ubiquitous in modern times. How does the emergence of generative artificial intelligence (AI), based on large language models (LLMs), fit into the IR process?
Journal of the American Medical Informatics Association : JAMIA
Sep 1, 2024
IMPORTANCE: The study highlights the potential of large language models, specifically GPT-3.5 and GPT-4, in processing complex clinical data and extracting meaningful information with minimal training data. By developing and refining prompt-based str...
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