Optimizing athletic performance through advanced nutrition strategies: can AI and digital platforms have a role in ultraendurance sports?

IF 4.2 2区 医学 Q1 SPORT SCIENCES Biology of Sport Pub Date : 2024-10-01 Epub Date: 2024-07-23 DOI:10.5114/biolsport.2024.141063
Luca Puce, Halil İbrahim Ceylan, Carlo Trompetto, Filippo Cotellessa, Cristina Schenone, Lucio Marinelli, Piotr Zmijewski, Nicola Luigi Bragazzi, Laura Mori
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Abstract

Nutrition is vital for athletic performance, especially in ultra-endurance sports, which pose unique nutritional challenges. Despite its importance, there exist gaps in the nutrition knowledge among athletes, and emerging digital tools could potentially bridge this gap. The ULTRA-Q, a sports nutrition questionnaire adapted for ultra-endurance athletes, was used to assess the nutritional knowledge of ChatGPT-3.5, ChatGPT-4, Google Bard, and Microsoft Copilot. Their performance was compared with experienced ultra-endurance athletes, registered sports nutritionists and dietitians, and the general population. ChatGPT-4 demonstrated the highest accuracy (93%), followed by Microsoft Copilot (92%), Bard (84%), and ChatGPT-3.5 (83%). The averaged AI model achieved an overall score of 88%, with the highest score in Body Composition (94%) and the lowest in Nutrients (84%). The averaged AI model outperformed the general population by 31% points and ultra-endurance athletes by 20% points in overall knowledge. The AI model exhibited superior knowledge in Fluids, outperforming registered dietitians by 49% points, the general population by 42% points, and ultra-endurance athletes by 32% points. In Body Composition, the AI model surpassed the general population by 31% points and ultraendurance athletes by 24% points. In Supplements, it outperformed registered dietitians by 58% points and the general population by 55% points. Finally, in Nutrients and in Recovery, it outperformed the general population only, by 24% and 29% points, respectively. AI models show high proficiency in sports nutrition knowledge, potentially serving as valuable tools for nutritional education and advice. AI-generated insights could be integrated with expert human judgment for effective athlete performance optimization.

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通过先进的营养策略优化运动表现:人工智能和数字平台能否在超级耐力运动中发挥作用?
营养对运动成绩至关重要,尤其是在超耐力运动中,这对营养提出了独特的挑战。尽管营养非常重要,但运动员在营养知识方面仍存在差距,而新兴的数字工具有可能弥补这一差距。ULTRA-Q是专为超耐力运动员设计的运动营养问卷,我们使用它来评估ChatGPT-3.5、ChatGPT-4、Google Bard和Microsoft Copilot的营养知识。他们的表现与经验丰富的超耐力运动员、注册运动营养师和营养师以及普通人进行了比较。ChatGPT-4 的准确率最高(93%),其次是 Microsoft Copilot(92%)、Bard(84%)和 ChatGPT-3.5(83%)。平均人工智能模型的总体得分率为 88%,其中身体成分得分率最高(94%),营养素得分率最低(84%)。平均人工智能模型在总体知识方面比普通人高出 31%,比超耐力运动员高出 20%。人工智能模型在体液知识方面表现优异,比注册营养师高出 49%,比普通人高出 42%,比超级耐力运动员高出 32%。在身体成分方面,人工智能模型比普通人高出 31%,比超级耐力运动员高出 24%。在营养补充剂方面,AI 模型比注册营养师高出 58%,比普通人高出 55%。最后,在 "营养素 "和 "恢复 "方面,它只比普通人高出 24% 和 29%。人工智能模型在运动营养知识方面表现出很高的熟练程度,有可能成为营养教育和建议的重要工具。人工智能生成的见解可与人类专家的判断相结合,从而有效优化运动员的表现。
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来源期刊
Biology of Sport
Biology of Sport 生物-运动科学
CiteScore
8.20
自引率
12.50%
发文量
113
审稿时长
>12 weeks
期刊介绍: Biology of Sport is the official journal of the Institute of Sport in Warsaw, Poland, published since 1984. Biology of Sport is an international scientific peer-reviewed journal, published quarterly in both paper and electronic format. The journal publishes articles concerning basic and applied sciences in sport: sports and exercise physiology, sports immunology and medicine, sports genetics, training and testing, pharmacology, as well as in other biological aspects related to sport. Priority is given to inter-disciplinary papers.
期刊最新文献
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