Harnessing Large Language Models in Medical Research and Scientific Writing: A Closer Look to The Future

Mohammad Abu-Jeyyab, Sallam Alrosan, I. Alkhawaldeh
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引用次数: 0

Abstract

Large Language Models (LLMs), a form of artificial intelligence generating natural language responses based on user input, have demonstrated potential across various applications such as entertainment, education, and customer service. This review comprehensively highlights their current research status and potential applications within the medical domain, addressing the challenges and opportunities for future development and implementation. Key aspects covered include diverse data sources for training and testing, such as electronic health records and clinical trials; ethical considerations, including privacy and consent; evaluation techniques focusing on accuracy and coherence; and clinical applications ranging from diagnosis to patient education. The review concludes that LLMs hold significant promise for enhancing the quality and efficiency of medical research and scientific writing but also emphasize the need for careful design and regulation to ensure safety and reliability.
在医学研究和科学写作中利用大型语言模型:展望未来
大型语言模型(llm)是一种基于用户输入生成自然语言响应的人工智能形式,已经在娱乐、教育和客户服务等各种应用中展示了潜力。本文综合介绍了它们在医学领域的研究现状和潜在应用,阐述了未来发展和实施的挑战和机遇。涉及的关键方面包括培训和测试的各种数据源,如电子健康记录和临床试验;道德考虑,包括隐私和同意;注重准确性和连贯性的评价技术;临床应用范围从诊断到患者教育。该审查的结论是,法学硕士在提高医学研究和科学写作的质量和效率方面具有重大前景,但也强调需要仔细设计和监管,以确保安全性和可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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