与ChatGPT一起走向素食:为个性化生活方式的改变设计法学硕士

IF 4.9
Munachiso Okenyi , Grace Ataguba , Kosi Clinton Henry , Sussan Anukem , Rita Orji
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引用次数: 0

摘要

大型语言模型(llm)是最近的技术革命之一,已经适用于人类努力的所有领域,包括健康。在健康领域,法学硕士为疾病管理、诊断、压力管理和其他与生活方式相关的重大改变做出了贡献。然而,对于它们在与糖尿病、心血管疾病、肥胖等疾病相关的营养和生活方式改变方面的影响,我们知之甚少。在本文中,我们介绍了ChatGPT作为LLM干预的两个案例研究,用于制定与生活方式相关的决策,例如过渡到素食生活方式:体重正常(健康);肥胖。此外,我们考虑了三(3)种饮食限制,这些限制可能会影响两个案例研究中的人们向素食生活方式的转变。包括:1)对坚果过敏;2)麸质过敏;3)没有过敏。我们使用ChatGPT根据这些饮食限制来生成一周(七天)的饮食计划。我们分析了ChatGPT的所有回复,发现ChatGPT提供了丰富的纯素饮食组合,并在一定程度上对这些食物过敏敏感。此外,我们发现了一些挑战,涉及如何使用适当的提示来优化ChatGPT的推荐和与ChatGPT推荐的食物总卡路里相关的精度。此外,我们提供了在未来工作中克服这些挑战的建议,包括支持用户特定领域的读写能力和对对人类健康有总体影响的指标的精确灵敏度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Going vegan with ChatGPT: Towards designing LLMs for personalized lifestyle changes
Large language models (LLMs), one of the recent technological revolutions, have become applicable to all areas of human endeavor, including health. In the area of health, LLMs have contributed to disease management, diagnosis, stress management, and other major lifestyle-related changes. However, little is yet known about their impact in the area of nutrition and lifestyle-related changes associated with diseases such as diabetes, cardiovascular diseases, obesity, and others. In this paper, we present two case studies of ChatGPT as an LLM intervention for making lifestyle-related decisions, such as transitioning to a vegan lifestyle: 1. normal weight (healthy) and 2. obesity. Additionally, we considered three (3) dietary restrictions that could affect people in both case studies to transition to a vegan lifestyle. These include 1) allergies to nuts; 2) allergies to gluten; and 3) no allergies. We used ChatGPT to generate a one-week (seven-day) meal plan based on these dietary restrictions. We analyzed all responses from ChatGPT and found that ChatGPT provides a rich combination of vegan diets and is sensitive to these food allergies to some extent. Additionally, we found some challenges that relate to how an appropriate prompt can be employed to optimize ChatGPT’s recommendations and precisions relating to the total calories of foods recommended by ChatGPT. Furthermore, we provide recommendations to overcome these challenges in future work, including supporting user's domain-specific literacy and precision sensitivity for metrics that have an overall impact on human health.
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来源期刊
Machine learning with applications
Machine learning with applications Management Science and Operations Research, Artificial Intelligence, Computer Science Applications
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