NVIDIA's "Chat with RTX" Custom Large Language Model and Personalized AI Chatbot Augments the Value of Electronic Dermatology Reference Material.

Q3 Medicine JMIR dermatology Pub Date : 2024-07-24 DOI:10.2196/58396
Maged N Kamel Boulos, Robert Dellavalle
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引用次数: 0

Abstract

This paper demonstrates a new, promising method using generative artificial intelligence (AI) to augment the educational value of electronic textbooks and research papers (locally stored on user's machine) and maximize their potential for self-study, in a way that goes beyond the standard electronic search and indexing that is already available in all of these textbooks and files. The presented method runs fully locally on the user's machine, is generally affordable, and does not require high technical expertise to set up and customize with the user's own content.

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英伟达™(NVIDIA®)的 "与 RTX 聊天 "定制大型语言模型和个性化人工智能聊天机器人提高了电子皮肤病学参考资料的价值。
本文展示了一种使用生成式人工智能(AI)的前景广阔的新方法,该方法可增强电子教科书和研究论文(本地存储在用户机器上)的教育价值,并最大限度地发挥其自学潜力,其方式超越了所有这些教科书和文件中已有的标准电子搜索和索引。所介绍的方法完全在用户的机器上本地运行,价格一般比较低廉,而且不需要很高的专业技术知识来设置和定制用户自己的内容。
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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来源期刊
CiteScore
1.20
自引率
0.00%
发文量
0
审稿时长
18 weeks
期刊最新文献
The Comparative Sufficiency of ChatGPT, Google Bard, and Bing AI in Answering Diagnosis, Treatment, and Prognosis Questions About Common Dermatological Diagnoses. The Depth Estimation and Visualization of Dermatological Lesions: Development and Usability Study. Dermatology in Student-Run Clinics in the United States: Scoping Review. Improving Affordability in Dermatology: Cost Savings in Mark Cuban Cost Plus Drug Company Versus GoodRx. Dermatologic Data From the Global Burden of Disease Study 2019 and the PatientsLikeMe Online Support Community: Comparative Analysis.
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