胃肠道疾病中的遗传人工智能:系统性审查
1AI Center, Korea University Anam Hospital, Seoul 02841, Republic of Korea.
Diagnostics (Basel, Switzerland)
|September 13, 2025
概括
基因人工智能通过分析单核酸多态 (SNP) 数据,显示出早期胃肠道疾病 (GID) 诊断的前景. 本次审查强调了其作为非侵入性决策支持工具的有效性.
科学领域:
- 生物信息学是一种生物信息学.
- 遗传学 是一个遗传学.
- 人工智能的人工智能
背景情况:
- 预测和可解释的人工智能越来越多地应用于生物信息学数据,包括单核酸多态 (SNP) 信息,用于疾病诊断.
- 需要对遗传AI在胃肠道疾病 (GID) 早期诊断方面的进展进行审查.
研究的目的:
- 系统地审查最近在应用遗传人工智能的进展,以早期诊断胃肠道疾病.
主要方法:
- 从2010年开始在PubMed上发表的十项原始研究的系统综述.
- 研究包括GID或相关疾病作为依赖变量,人工智能作为干预,准确性,AUC或变量重要性作为结果.
- 考虑了英语出版物.
主要成果:
- 性能指标各不相同,准确度在79-100%之间,曲线下的面积 (AUC) 在63-98%之间.
- 随机森林模型表现出高性能,在炎症性肠病分类中达到98%的AUC,在肠道微生物组SNP回归中达到99%的R平方.
- 关键的SNP和其他因素,如年龄,BMI和微生物组被确定为GID的重要预测因素.
结论:
- 基因人工智能作为诊断胃肠道疾病的有效和非侵入性决策支持系统.
- 该审查确定了重要的SNP和其他变量,这些变量对于预测GID至关重要,尽管没有发现深度学习研究.
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