智能微生物组:人工智能如何彻底改变个性化医学
Luana Alexandrescu1,2, Ionut Tiberiu Tofolean1,2, Laura Maria Condur2
1Gastroenterology Department, "Sf. Apostol Andrei" Emergency County Hospital, 145 Tomis Blvd., 900591 Constanta, Romania.
Bioengineering (Basel, Switzerland)
|September 27, 2025
概括
机器学习有助于理解肠道微生物群.
科学领域:
- 微生物组研究和计算生物学.
背景情况:
- 肠道微生物群在人类健康和疾病中起着至关重要的作用.
- 高通量技术产生了大量的微生物数据.
研究的目的:
- 审查肠道微生物群与人类疾病之间的关系.
- 探索机器学习应用在分析肠道微生物群数据.
- 讨论机器学习在开发向治疗中的潜力.
主要方法:
- 分析有关肠道微生物群和机器学习的现有文献.
- 机器学习方法的分类和工作流程解释.
- 使用机器学习进行多学科数据集成的审查.
主要成果:
- 肠道微生物群失调与各种人类疾病有关.
- 机器学习算法有效地识别微生物组数据中的分子签名.
- 机器学习促进了对多学科数据的综合分析.
结论:
- 机器学习非常适合用于肠道微生物组分析.
- 机器学习方法可以指导肠道微生物向治疗的开发.
- 这些方法有助于个性化和精准医学.
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