Bettina Hieronimus , Simon Hammann , Maren C. Podszun
{"title":"人工智能工具 ChatGPT 和 Bard 能否为不同的饮食模式生成能量、宏量和微量营养素充足的膳食计划?","authors":"Bettina Hieronimus , Simon Hammann , Maren C. Podszun","doi":"10.1016/j.nutres.2024.07.002","DOIUrl":null,"url":null,"abstract":"<div><p>Artificial intelligence chatbots based on large language models have recently emerged as an alternative to traditional online searches and are also entering the nutrition space. In this study, we wanted to investigate whether the artificial intelligence chatbots ChatGPT and Bard (now Gemini) can create meal plans that meet the dietary reference intake (DRI) for different dietary patterns. We further hypothesized that nutritional adequacy could be improved by modifying the prompts used. Meal plans were generated by 3 accounts for different dietary patterns (omnivorous, vegetarian, and vegan) using 2 distinct prompts resulting in 108 meal plans total. The nutrient content of the plans was subsequently analyzed and compared to the DRIs. On average, the meal plans contained less energy and carbohydrates but mostly exceeded the DRI for protein. Vitamin D and fluoride fell below the DRI for all plans, whereas only the vegan plans contained insufficient vitamin B<sub>12</sub>. ChatGPT suggested using vitamin B<sub>12</sub> supplements in 5 of 18 instances, whereas Bard never recommended supplements. There were no significant differences between the prompts or the tools. Although the meal plans generated by ChatGPT and Bard met most DRIs, there were some exceptions, particularly for vegan diets. These tools maybe useful for individuals looking for general dietary inspiration, but they should not be relied on to create nutritionally adequate meal plans, especially for individuals with restrictive dietary needs.</p></div>","PeriodicalId":19245,"journal":{"name":"Nutrition Research","volume":"128 ","pages":"Pages 105-114"},"PeriodicalIF":3.4000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0271531724000915/pdfft?md5=bf93e7d5f008fb898fce35dcd948d075&pid=1-s2.0-S0271531724000915-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Can the AI tools ChatGPT and Bard generate energy, macro- and micro-nutrient sufficient meal plans for different dietary patterns?\",\"authors\":\"Bettina Hieronimus , Simon Hammann , Maren C. Podszun\",\"doi\":\"10.1016/j.nutres.2024.07.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Artificial intelligence chatbots based on large language models have recently emerged as an alternative to traditional online searches and are also entering the nutrition space. In this study, we wanted to investigate whether the artificial intelligence chatbots ChatGPT and Bard (now Gemini) can create meal plans that meet the dietary reference intake (DRI) for different dietary patterns. We further hypothesized that nutritional adequacy could be improved by modifying the prompts used. Meal plans were generated by 3 accounts for different dietary patterns (omnivorous, vegetarian, and vegan) using 2 distinct prompts resulting in 108 meal plans total. The nutrient content of the plans was subsequently analyzed and compared to the DRIs. On average, the meal plans contained less energy and carbohydrates but mostly exceeded the DRI for protein. Vitamin D and fluoride fell below the DRI for all plans, whereas only the vegan plans contained insufficient vitamin B<sub>12</sub>. ChatGPT suggested using vitamin B<sub>12</sub> supplements in 5 of 18 instances, whereas Bard never recommended supplements. There were no significant differences between the prompts or the tools. Although the meal plans generated by ChatGPT and Bard met most DRIs, there were some exceptions, particularly for vegan diets. These tools maybe useful for individuals looking for general dietary inspiration, but they should not be relied on to create nutritionally adequate meal plans, especially for individuals with restrictive dietary needs.</p></div>\",\"PeriodicalId\":19245,\"journal\":{\"name\":\"Nutrition Research\",\"volume\":\"128 \",\"pages\":\"Pages 105-114\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0271531724000915/pdfft?md5=bf93e7d5f008fb898fce35dcd948d075&pid=1-s2.0-S0271531724000915-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nutrition Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0271531724000915\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NUTRITION & DIETETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nutrition Research","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0271531724000915","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NUTRITION & DIETETICS","Score":null,"Total":0}
Can the AI tools ChatGPT and Bard generate energy, macro- and micro-nutrient sufficient meal plans for different dietary patterns?
Artificial intelligence chatbots based on large language models have recently emerged as an alternative to traditional online searches and are also entering the nutrition space. In this study, we wanted to investigate whether the artificial intelligence chatbots ChatGPT and Bard (now Gemini) can create meal plans that meet the dietary reference intake (DRI) for different dietary patterns. We further hypothesized that nutritional adequacy could be improved by modifying the prompts used. Meal plans were generated by 3 accounts for different dietary patterns (omnivorous, vegetarian, and vegan) using 2 distinct prompts resulting in 108 meal plans total. The nutrient content of the plans was subsequently analyzed and compared to the DRIs. On average, the meal plans contained less energy and carbohydrates but mostly exceeded the DRI for protein. Vitamin D and fluoride fell below the DRI for all plans, whereas only the vegan plans contained insufficient vitamin B12. ChatGPT suggested using vitamin B12 supplements in 5 of 18 instances, whereas Bard never recommended supplements. There were no significant differences between the prompts or the tools. Although the meal plans generated by ChatGPT and Bard met most DRIs, there were some exceptions, particularly for vegan diets. These tools maybe useful for individuals looking for general dietary inspiration, but they should not be relied on to create nutritionally adequate meal plans, especially for individuals with restrictive dietary needs.
期刊介绍:
Nutrition Research publishes original research articles, communications, and reviews on basic and applied nutrition. The mission of Nutrition Research is to serve as the journal for global communication of nutrition and life sciences research on diet and health. The field of nutrition sciences includes, but is not limited to, the study of nutrients during growth, reproduction, aging, health, and disease.
Articles covering basic and applied research on all aspects of nutrition sciences are encouraged, including: nutritional biochemistry and metabolism; metabolomics, nutrient gene interactions; nutrient requirements for health; nutrition and disease; digestion and absorption; nutritional anthropology; epidemiology; the influence of socioeconomic and cultural factors on nutrition of the individual and the community; the impact of nutrient intake on disease response and behavior; the consequences of nutritional deficiency on growth and development, endocrine and nervous systems, and immunity; nutrition and gut microbiota; food intolerance and allergy; nutrient drug interactions; nutrition and aging; nutrition and cancer; obesity; diabetes; and intervention programs.