开放科学实践需要在使用机器学习的瘤学预后模型研究中大幅度改进
Gary S Collins1, Rebecca Whittle1, Garrett S Bullock2
1Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Centre for Statistics in Medicine, University of Oxford, Oxford, United Kingdom.
Journal of clinical epidemiology
|October 28, 2023
概括
开放科学实践很少在瘤学研究中使用,开发机器学习预后模型. 需要提高意识和指导,以改善数据和代码共享,以便更好地进行预测研究.
科学领域:
- 在瘤学瘤学.
- 机器学习 机器学习
- 预测模型的预测建模
- 开放科学是一个开放的科学.
背景情况:
- 机器学习 (ML) 越来越多地用于开发瘤学的预后模型.
- 开放科学实践对于研究中的透明度,可重复性和协作至关重要.
研究的目的:
- 评估当代瘤学研究中开放科学实践的频率,开发基于ML的预后模型.
- 确定改善开放科学在这个领域的采用障碍和机会.
主要方法:
- 对开发ML预后模型的瘤学研究进行系统审查.
- 在MEDLINE数据库中搜索 (2022年12月1日至31日).
- 两个作者对开放科学实践进行了独立的选和数据提取.
主要成果:
- 只有46个出版物符合纳入标准.
- 采用开放科学原则的程度较低:协议注册 (1项研究),数据共享 (4%),代码共享 (4%).
- 报告准则的使用很少 (18%),仅限于遵守TRIPOD或MI-CLARE等特定准则.
结论:
- 在瘤学ML预后建模中,开放科学的采用率很低.
- 需要加强对开放科学好处和最佳实践的指导和意识.
- 改进开放科学可以促进瘤学的预测研究.
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