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修剪如何影响长尾多标签医学图像分类器?

Gregory Holste¹, Ziyu Jiang², Ajay Jaiswal¹

¹The University of Texas at Austin, Austin, TX, USA.

|October 4, 2023

概括

用于医学图像诊断的神经网络修剪可以改变模型行为,特别是在罕见疾病中. 放射科医生发现修剪模型不一致 (PIEs) 难以诊断,这表明需要谨慎部署.

科学领域:

人工智能的人工智能
医疗成像医学成像
计算机视觉计算机视觉

背景情况:

深度神经网络修剪可以减少模型大小和推断时间.
修剪对长尾,多标签临床数据模型的影响不太清楚.
这种差距给医疗保健中的诊断模型部署带来了风险.

结论:

这项研究是首次分析修剪对多标签CXR诊断神经网络的影响.
这些发现凸显了在临床AI部署中仔细考虑修剪的必要性.
了解修剪的影响对于安全可靠的医疗AI至关重要.

关键词:

胸部X射线胸部X射线这是不平衡的失衡.长尾学习长尾学习修剪修剪修剪修剪

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