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机器学习算法的性能在MRI上区分神经炎特征:系统性审查

Sun Jae Moon¹, Seulkee Lee², Jinseub Hwang³

¹Department of Medicine, Santa Marie 24 Clinic, Seongnam-si, Korea (the Republic of).

|November 23, 2023

概括

机器学习算法在MRI扫描上检测神经炎时,表现与放射科医生相当. 然而,研究异质性和偏见限制了当前的证据,需要进一步研究.

科学领域:

放射学和医学成像学医学成像学
人工智能在医学中的应用
类风湿病学类风湿病学

背景情况:

机器学习 (ML) 算法越来越多地被用于医学图像分析,特别是在风湿病学中用于诊断诸如神经炎等疾病.
在磁共振成像 (MRI) 上区分神经关节炎特征对于早期发现脊椎关节炎至关重要.
本综述综合了与人类医生相比,在圣炎检测中ML性能方面的证据.

结论:

在MRI上检测神经炎的ML算法的性能是可变的,受研究异质性和方法限制的影响.
样本规模较小,过度配合和报告不足的问题影响了当前调查结果的可靠性.
进一步的精心设计,透明的研究是必不可少的,以确定ML在圣炎诊断中的最终作用.

关键词:

流行病学流行病学机器学习机器学习磁共振成像是一种磁共振成像技术.脊椎炎,结性脊柱炎,结性脊柱炎,结性脊柱炎,结性脊柱炎,结性脊柱炎,结性脊柱炎,结性脊柱炎,结性脊柱炎,结性脊柱炎,结性脊柱炎.

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