Harnessing AI and Gut Microbiome Research for Precision Health

Ritcha Saxena, Vikas Sharma, Ananya Saxena, Aakash Patel
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Abstract

The gut microbiome's impact on physiological processes, influenced by diet and lifestyle, is profound. Dysbiosis, an imbalance in microbiota composition, is associated with diseases like obesity. This review explores the gut microbiome's role in metabolism and calorie intake, alongside recent AI advancements impacting personalized nutrition. AI has revolutionized microbiome research, especially in multi-omics data analysis. AI-driven approaches enable the integration and interpretation of diverse omics datasets, including genomics, metabolomics, and proteomics, providing comprehensive insights into the gut microbiome's functional dynamics and its impact on host metabolism. These facilitate the identification of microbial biomarkers associated with disease states and dietary interventions, paving the way for personalized nutrition strategies tailored to individual gut microbiome profiles. AI platforms can also offer tailored dietary recommendations based on microbiome composition and health objectives. Healthcare professionals leverage AI to optimize dietary interventions, promoting gut microbiome modulation and preventing chronic diseases. Challenges like data standardization and privacy persist, yet addressing them is vital for maximizing AI's benefits in health outcomes and precision medicine. Ongoing AI and microbiome research promise to revolutionize personalized nutrition and metabolic health worldwide.
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利用人工智能和肠道微生物组研究促进精准健康
肠道微生物群受饮食和生活方式的影响,对生理过程有着深远的影响。菌群失调(微生物群组成失衡)与肥胖等疾病有关。本综述将探讨肠道微生物组在新陈代谢和卡路里摄入中的作用,以及最近影响个性化营养的人工智能进展。人工智能为微生物组研究带来了革命性的变化,尤其是在多组学数据分析方面。人工智能驱动的方法能够整合和解释不同的组学数据集,包括基因组学、代谢组学和蛋白质组学,从而全面了解肠道微生物组的功能动态及其对宿主代谢的影响。这有助于确定与疾病状态和饮食干预相关的微生物生物标志物,为根据个体肠道微生物组特征制定个性化营养策略铺平道路。人工智能平台还可以根据微生物组的组成和健康目标提供量身定制的饮食建议。医疗保健专业人员可利用人工智能优化饮食干预,促进肠道微生物组调节,预防慢性疾病。数据标准化和隐私等挑战依然存在,但解决这些问题对于最大限度地发挥人工智能在健康成果和精准医疗方面的优势至关重要。正在进行的人工智能和微生物组研究有望彻底改变全球的个性化营养和代谢健康。
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