Minimization of occurrence of retained surgical items using machine learning and deep learning techniques: a review.

Autor: Abo-Zahhad M; Department of Electronics and Communications Engineering, Egypt-Japan University of Science and Technology, New Borg El-Arab City, Alexandria, Egypt. mohammed.zahhad@ejust.edu.eg.; Department of Electrical and Electronics Engineering, Assiut University, Assiut, Egypt. mohammed.zahhad@ejust.edu.eg., El-Malek AHA; Department of Electronics and Communications Engineering, Egypt-Japan University of Science and Technology, New Borg El-Arab City, Alexandria, Egypt., Sayed MS; Department of Electronics and Communications Engineering, Egypt-Japan University of Science and Technology, New Borg El-Arab City, Alexandria, Egypt.; Department of Electronics and Communications Engineering, Zagazig University, Zagazig, Egypt., Gitau SN; Department of Electronics and Communications Engineering, Egypt-Japan University of Science and Technology, New Borg El-Arab City, Alexandria, Egypt.

Publikováno v: BioData mining [BioData Min] 2024 Jun 18; Vol. 17 (1), pp. 17. Date of Electronic Publication: 2024 Jun 18.