Applications of the artificial bee colony algorithm in medical ‎imaging and diagnostics: a review - Ahmed Shaban, Awaz; Yasin, Hajar Maseeh (International Journal of Scientific World, 2025)
The Artificial Bee Colony algorithm is an innovative optimization technique inspired by the foraging behavior of honeybees. Its ability to ‎balance exploration and exploitation makes it effective for addressing complex challenges, particularly in medicine. This paper explores its ‎applications in medical image segmentation, disease detection, and biomedical signal processing. Notable achievements include improving ‎tumor segmentation in noisy MRI scans and enhancing disease classification. However, challenges like high computational demands and ‎scalability remain. Hybrid approaches, such as combining ABC with neural networks, show promise. Future research could focus on real-‎time healthcare applications and integrating ABC with the Internet of Medical Things. This study underscores the potential of ABC to drive ‎significant advancements in healthcare‎.