2024
DOI: 10.1371/journal.pone.0300622
|View full text |Cite
|
Sign up to set email alerts
|

An improved breast cancer classification with hybrid chaotic sand cat and Remora Optimization feature selection algorithm

Afnan M. Alhassan

Abstract: Breast cancer is one of the most often diagnosed cancers in women, and identifying breast cancer histological images is an essential challenge in automated pathology analysis. According to research, the global BrC is around 12% of all cancer cases. Furthermore, around 25% of women suffer from BrC. Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce finding… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
references
References 44 publications
0
0
0
Order By: Relevance