机器学习在治疗中的作用:系统审查协议
Richard Shek-Kwan Chang1, Shani Nguyen2, Zhibin Chen1
1Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia.
BMJ open
|January 25, 2024
概括
本系统审查协议概述了机器学习 (ML) 在管理中的使用. 它的目的是探索ML的ML.
科学领域:
- 神经学 神经学
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 机器学习 (ML) 越来越多地被整合到医疗应用中,包括诊断和临床决策支持.
- 尽管治疗方案取得了进展,症的治疗仍然存在挑战.
- 需要探索新的方法来优化病护理.
研究的目的:
- 系统地审查机器学习在临床管理中的作用.
- 确定ML如何有助于预测抗发作药物反应和耐药性.
- 评估ML在预测手术和神经调节的结果中的实用性.
主要方法:
- 一个系统审查协议,遵循系统审查和元分析 (PRISMA) 准则的首选报告项目.
- 在主要数据库 (MEDLINE,Embase,Scopus,Web of Science) 进行文献搜索.
- 专注于临床决策研究,使用已建立的数据提取检查清单和偏差风险评估.
主要成果:
- 本章节将介绍一旦数据提取和合成完成,系统审查的结果.
- 结果将重点关注ML模型在管理中的预测准确性和临床实用性.
- 包含的研究的质量评估将使用预测模型风险偏差评估工具 (PROBAST) 进行.
结论:
- 这些发现将阐明机器学习在管理中的当前状态和未来潜力.
- 这次审查将为临床医生和研究人员提供有关ML用于个性化治疗策略的应用的信息.
- 结果将通过同行评审的出版物和学术会议传播.
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