营养学中的人工智能:对功能性食品洞察力和个性化营养途径的批判性审查
Janani Balamurugan1, Samuel Ayofemi Olalekan Adeyeye1
1Department of Food Technology, Hindustan Institute of Technology and Science, Chennai, Tamil Nadu, India.
概括
人工智能 (AI) 正在通过基于遗传和生活方式数据实现个性化的营养计划来彻底改变营养基因组学. 人工智能工具增强对基因饮食相互作用的理解,以改善健康结果和疾病管理.
科学领域:
- 营养学和生物信息学
- 个性化医疗是个性化的医疗.
- 计算生物学 计算生物学
背景情况:
- 人工智能 (AI) 在营养基因组学中的应用得到了批判性评估.
- 专注于功能性食物-基因相互作用,个性化营养和基于证据的饮食干预措施.
- 旨在通过量身定制的营养策略改善健康结果.
研究的目的:
- 审查和综合营养基因组学当前的人工智能应用.
- 识别人工智能驱动的个性化营养的趋势,方法和研究缺口.
- 评估AI在功能性食品基因相互作用解释方面的潜力.
主要方法:
- 在主要数据库 (PubMed,Scopus,Web of Science,Google Scholar) 进行系统的文献搜索 (2010-2025年).
- 关键词:人工智能,营养基因组学,个性化营养,功能性食品.
- 在严格选后,对142项选定的研究进行了定性综合.
主要成果:
- 人工智能改变了营养基因组学,通过使用遗传,代谢和生活方式数据提供个性化的饮食建议.
- 机器学习和深度学习识别了复杂的基因饮食相互作用,改善了代谢和疾病结果的预测.
- 人工智能支持生物标志物发现,基因型指导和实时监测,用于管理肥胖,糖尿病和心血管疾病.
结论:
- 人工智能驱动的营养基因组学具有促进个性化营养的巨大潜力.
- 挑战包括算法偏见,数据隐私和道德治理.
- 方法的完善和负责任的实施是临床翻译和公平获取的关键.
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