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Evaluation of the performance of traditional machine learning algorithms convolutional neural network and AutoML Vision in ultrasound breast lesions classification: a comparative study

机译:超声乳房病变中传统机器学习算法卷积神经网络和自动视力的性能评价:比较研究

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摘要

In recent years, there was an increasing popularity in applying artificial intelligence in the medical field from computer-aided diagnosis (CAD) to patient prognosis prediction. Given the fact that not all healthcare professionals have the required expertise to develop a CAD system, the aim of this study was to investigate the feasibility of using AutoML Vision, a highly automatic machine learning model, for future clinical applications by comparing AutoML Vision with some commonly used CAD algorithms in the differentiation of benign and malignant breast lesions on ultrasound.
机译:近年来,在从计算机辅助诊断(CAD)到患者预后预测,在医疗领域应用人工智能越来越受欢迎。鉴于并非所有医疗专业人员都有所需的专业知识来开发CAD系统,本研究的目的是通过比较Automl Vision与一些人来调查使用自动化机器学习模型的自动化机器学习模型的可行性超声波对良性和恶性乳房病变的常用CAD算法。

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