Lightweight separable convolution network for breast cancer histopathological identification

HIGHLIGHTS

  • who: Grace Ugochi Nneji and collaborators from the Department of Computing, Oxford Brookes College of Chengdu University of Technology, Chengdu, China have published the research: Lightweight Separable Convolution Network for Breast Cancer Histopathological Identification, in the Journal: Diagnostics 2023, 13, 299. of /2023/
  • what: In this paper a lightweight separable convolution network (LWSC) is proposed to automatically learn and classify breast cancer from images. The model integrated different breast cancer risk rates, and different inputs are used to forecast a woman`s risk of acquiring breast cancer using logistics regression . The researchers utilized the Breast . . .

     

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