在脑研究中对机器学习方法进行系统审查
Anjuman Nahar1, Sudip Paul1, Manob Jyoti Saikia2,3
1Department of Biomedical Engineering, North-Eastern Hill University, Shillong, Meghalaya, India.
PeerJ
|October 22, 2024
概括
机器学习 (ML) 模型在脑 (CP) 研究中表现有前途,有助于识别,分类和预测. 临床数据是关键,但研究变异限制了概括性.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
背景情况:
- 大脑 (CP) 研究越来越多地利用机器学习 (ML) 模型.
- 在CP中ML的应用旨在改善识别,分类,异常预测和管理.
研究的目的:
- 审查脑 (CP) 的ML应用中的进展.
- 在CP识别,分类和预测中比较各种ML算法的性能.
- 检查ML对CP研究和治疗结果的影响.
主要方法:
- 对从2013年到2023年的20项研究进行了系统审查.
- 使用PubMed,IEEE Xplore,谷歌学者,Scopus和科学网络进行的搜索.
- 纳入标准集中在对CP患者应用的ML技术上,不包括未经同行评审的文章.
主要成果:
- 随机森林 (RF) 在分类CP运动和形方面表现出色.
- 一些ML算法,包括SVM,DT,RF和KNN,在运动评估中实现了100%的准确性.
- 神经网络通过眼睛图像在诊断CP时表现出94.17%的准确性.
结论:
- 在CP的ML模型中,临床数据构成了主要输入 (47%).
- 人们对CP研究的自动化,数据驱动的ML方法越来越感兴趣.
- 研究设计和数据质量的变化需要谨慎对待概括性.
相关概念视频
01:22Machines: Problem Solving I
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
01:30Machines: Problem Solving II
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.