使用gpt驱动的AI聊天机器人生成个性化孕期营养建议

Chun-Hua Tsai, Sathvik Kadire, Tejesvi Sreeramdas, M. VanOrmer, M. Thoene, C. Hanson, A. Berry, Deepak Khazanchi
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引用次数: 1

摘要

低社会经济地位(SES)和怀孕期间营养不足与健康差距和不良后果有关,包括早产、低出生体重和宫内生长受限的风险增加。人工智能驱动的计算代理具有巨大的潜力,可以通过向具有不同健康素养和人口统计学特征的患者提供营养指南或建议来应对这一挑战。本文介绍了我们对创建一个名为NutritionBot的gpt人工智能聊天机器人的初步探索,并调查了怀孕营养建议的影响。我们使用以用户为中心的设计方法来定义目标用户角色,并与医疗专业人员合作共同设计聊天机器人。我们将我们提出的聊天机器人与ChatGPT结合起来,根据患者的生活方式生成孕期营养建议。我们的贡献包括从服务不足的人群中引入孕妇的设计角色,与医疗保健专家共同设计营养建议聊天机器人,并根据我们的初步发现分享未来基于gpt的营养聊天机器人的设计含义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generating Personalized Pregnancy Nutrition Recommendations with GPT-Powered AI Chatbot
Low socioeconomic status (SES) and inadequate nutrition during pregnancy are linked to health disparities and adverse outcomes, including an increased risk of preterm birth, low birth weight, and intrauterine growth restriction. AI-powered computational agents have enormous potential to address this challenge by providing nutrition guidelines or advice to patients with different health literacy and demographics. This paper presents our preliminary exploration of creating a GPT-powered AI chatbot called NutritionBot and investigates the implications for pregnancy nutrition recommendations. We used a user-centered design approach to define the target user persona and collaborated with medical professionals to co-design the chatbot. We integrated our proposed chatbot with ChatGPT to generate pregnancy nutrition recommendations tailored to patients’ lifestyles. Our contributions include introducing a design persona of a pregnant woman from an underserved population, co-designing a nutrition advice chatbot with healthcare experts, and sharing design implications for future GPT-based nutrition chatbots based on our preliminary findings.
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