Overview of the proposed deep learning and feature selection framework for bone marrow cell classification.

<p>Overview of the proposed deep learning and feature selection framework for bone marrow cell classification.</p>

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Bibliographic Details
Main Author:	Doaa Sami Khafaga (21463870) (author)
Other Authors:	El-Sayed M. El-kenawy (14581088) (author), Faris H. Rizk (21755909) (author), Marwa M. Eid (11251630) (author), Ehsaneh Khodadadi (22146329) (author), Nima Khodadadi (14581091) (author)
Published:	2025
Subjects:	Biotechnology Sociology Hematology Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified false negative rate effective feature selection driven deep learning deep learning models contributions include developing clinical diagnostics quantifiably average classification error automated cytology technology optimization also results metaheuristic optimization techniques enhancing cnn performance ocoa ), designed increases cnn accuracy ocotillo optimization hyperparameter optimization study introduces significantly reduced sensitivity increasing maximum accuracy innovative bio initial accuracy highly dependent findings highlight expert knowledge critical scenarios continuous version binary variant accurate solution 61 %), 48 %. 24 %. (+ 12 (+ 11
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