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人工智能在药物相互作用预测中的应用:一篇评论
Yuanyuan Zhang1, Zengqian Deng1, Xiaoyu Xu1
1School of Information and Control Engineering, Qingdao University of Technology, Qingdao,266000,China.
Journal of chemical information and modeling
|July 17, 2023
概括
人工智能 (AI) 推进了药物相互作用 (DDI) 的预测,提高了患者的安全性. 本综述对DDI预测任务进行了分类,并总结了AI方法,数据集和临床决策的未来前景.
科学领域:
- 药理学和生物信息学 药理学和生物信息学
- 人工智能在医学中的应用
背景情况:
- 药物相互作用 (DDI) 对患者的安全性和治疗疗效构成重大风险.
- 手动检测DDI是劳动密集型和耗时的,需要先进的预测方法.
- 准确的DDI预测有助于临床医生优化治疗方案并改善患者的治疗结果.
研究的目的:
- 为预测药物相互作用 (DDI) 提供人工智能 (AI) 应用的全面概述.
- 将DDI预测任务分为非定向,事件和不对称的预测类型.
- 审查当前的AI技术,数据集和DDI预测中的挑战.
主要方法:
- 将DDI预测分为三个主要类型:非定向的DDI事件和不对称的预测.
- 对常用的数据库和用于DDI预测的经典机器学习技术进行审查.
- 在不同DDI预测任务中分析代表性AI方法和数据集.
主要成果:
- 关于人工智能的进展总结 非定向DDI预测,DDI事件预测和不对称DDI预测.
- 对数据集和在现场使用的代表机器学习和人工智能方法的概述.
- 在人工智能驱动的DDI预测中识别趋势和进展.
结论:
- 人工智能提供了一种强大的方法来准确预测DDI,克服手动检测的局限性.
- 该审查强调了人工智能在增强临床决策和提高患者安全方面的潜力.
- 讨论了基于AI的DDI预测的未来研究方向和挑战.
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