Bone metastasis detection method based on improving golden jackal optimization using whale optimization algorithm.

Autor: Magdy O; Applied Mathematical Physics Research Group, Physics Department, Faculty of Science, Mansoura University, Mansoura, 35516, Egypt., Abd Elaziz M; Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, 44519, Egypt. abd_el_aziz_m@yahoo.com.; Faculty of Computer Science and Engineering, Galala University, Suez, 435611, Egypt. abd_el_aziz_m@yahoo.com.; Artificial Intelligence Research Center (AIRC), Ajman University, Ajman, UAE. abd_el_aziz_m@yahoo.com.; Department of Electrical and Computer Engineering, Lebanese American University, Byblos, Lebanon. abd_el_aziz_m@yahoo.com.; MEU Research Unit, Middle East University, Amman, Jordan. abd_el_aziz_m@yahoo.com., Elgarayhi A; Applied Mathematical Physics Research Group, Physics Department, Faculty of Science, Mansoura University, Mansoura, 35516, Egypt., Ewees AA; Department of Computer, Damietta University, Damietta, 34517, Egypt. ewees@du.edu.eg., Sallah M; Applied Mathematical Physics Research Group, Physics Department, Faculty of Science, Mansoura University, Mansoura, 35516, Egypt.; Department of Physics, College of Sciences, University of Bisha, P.O. Box 344, Bisha , 61922, Saudi Arabia.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2023 Sep 12; Vol. 13 (1), pp. 15019. Date of Electronic Publication: 2023 Sep 12.
DOI: 10.1038/s41598-023-41733-x
Abstrakt: This paper presents a machine learning-based technique for interpreting bone scintigraphy images, focusing on feature extraction and introducing a new feature selection method called GJOW. GJOW enhances the effectiveness of the golden jackal optimization (GJO) algorithm by integrating operators from the whale optimization algorithm (WOA). The technique's performance is evaluated through extensive experiments using 18 benchmark datasets and 581 bone scan images obtained from a gamma camera, including 362 abnormal and 219 normal cases. The results highlight the superior predictive effectiveness of the GJOW algorithm in bone metastasis detection, achieving an accuracy of 71.79% and specificity of 91.14%. The contributions of this study include the introduction of a new machine learning-based approach for detecting bone metastasis using gamma camera scans, leading to improved accuracy in identifying bone metastases. The findings have practical implications for early detection and intervention, potentially improving patient outcomes.
(© 2023. Springer Nature Limited.)
Databáze: MEDLINE
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