临床试验中的机器学习:一本关于神经病学应用的入门书
Matthew I Miller1, Ludy C Shih2, Vijaya B Kolachalama3,4
1Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, 72 E. Concord Street, Evans 636, Boston, MA, 02118, USA.
概括
人工智能 (AI) 和机器学习 (ML) 可以显著改善临床试验,特别是神经疾病. 这些技术为更快的招聘,更好的试验模拟和增强的远程监控提供了解决方案,尽管广泛采用仍然存在挑战.
科学领域:
- 临床研究方法论临床研究方法论
- 医学中的人工智能
- 机器学习应用程序 机器学习应用程序
背景情况:
- 审查了人工智能 (AI) 和机器学习 (ML) 的基本概念.
- 探索AI和ML在推进临床试验和研究方面的潜力.
- 特别注意的是用于设计,进行和解释神经疾病临床试验的应用.
结论:
- 将ML整合到临床试验工作流程中,有望取得重大进展.
- 解决技术,管理和监管方面的挑战对于成功采用ML至关重要.
- 未来的研究应该专注于克服这些障碍,以充分利用临床研究中的ML.
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