人工智能和机器学习在药物重用中的应用
Sudhir K Ghandikota1, Anil G Jegga2
1Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
概括
药物再利用利用现有药物治疗新疾病,为精准医学提供更快,更便宜的途径. 先进的AI和机器学习加速了这一过程,识别了罕见疾病的治疗方法.
科学领域:
- 药理学 药理学是指药理学的学科.
- 生物医学信息学 生物医学信息学
- 计算生物学 计算生物学
背景情况:
- 药物重新定位通过确定现有药物的新用途来加速药物发现.
- 这是一个具有成本效益的战略,支持精准医学和治疗罕见疾病.
- 有限的疾病生物学信息往往阻碍了治疗候选者的识别.
研究的目的:
- 审查药物重用方面的挑战和成功.
- 根据数据类型和算法,对药物重定向的计算框架进行调查.
- 探索由人工智能驱动的未来方向.
主要方法:
- 审查现有的关于药物重定向方法的文献.
- 分析使用异质网络挖矿和自然语言处理的计算框架.
- 使用机器学习和人工智能集成和分析大规模的生物医学数据.
主要成果:
- 药物重定向提供了一个更快,更具成本效益的药物发现途径.
- 机器学习和人工智能增强了数据驱动的重定向管道.
- 技术进步提供了新的分析策略,用于识别治疗候选药物.
结论:
- 药物重新定位是精准医学和罕见疾病的重要工具.
- 人工智能和机器学习正在改变计算药物重定向.
- 生成性人工智能准备在药物重用研究中推动未来的创新.
关键词:
人工智能的人工智能在新的药物发现中,新的药物被发现.深度学习 (Deep Learning) 是一种深度学习.药物重新定位 药物重新定位药物重新定位是药物重新定位.机器学习 机器学习网络分析 网络分析更多相关视频
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