Breast cancer classification depends on the dynamic dipper throated optimization algorithm

HIGHLIGHTS

  • who: Amel Ali Alhussan and collaborators from the Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, POBox, Riyadh, Saudi Arabia have published the paper: Breast Cancer Classification Depends on the Dynamic Dipper Throated Optimization Algorithm, in the Journal: Biomimetics 2023, 8, 163. of /2023/
  • what: This research proposes a novel framework integrating metaheuristic optimization with deep learning and feature selection for robustly classifying cancer from ultrasound images. Within the scope of this paper, the following issues are examined: (i) In this work, four classifiers are evaluated to choose . . .

     

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