计算机科学
人工智能
深度学习
乳腺癌
透视图(图形)
临床实习
机器学习
模式识别(心理学)
上下文图像分类
癌症
图像(数学)
医学
内科学
家庭医学
作者
Rui Yan,Fei Ren,Xiaosong Rao,Baorong Shi,Tiange Xiang,Lingling Zhang,Yudong Liu,Jun Liang,Chun-Hou Zheng,Fa Zhang
标识
DOI:10.1007/978-3-030-26763-6_44
摘要
Although the application of deep learning has greatly improved the performance of benign and malignant breast cancer classification algorithm, the accuracy of classification using only the pathological image has been unable to meet the requirements of clinical practice. Inspired by the real scene when the pathologist read the pathological image for diagnosis, in this paper, we propose a new hybrid deep learning method for benign and malignant breast cancer classification. From the perspective of multimodal data fusion, our method combines pathological image and structured data in the clinical electronic medical record (EMR) to further improve the accuracy of breast cancer classification. Thus, the proposed method can be useful for breast cancer diagnosis in real clinical practice. Experimental results based on our datasets show that the proposed method significantly outperforms the state-of-the-art methods in terms of overall classification accuracy.
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