Fatimaelzahraa Ali Ahmed
Papers
1
Total Citations
35
H-Index
1
About
Fatimaelzahraa Ali Ahmed is a leading researcher at the intersection of artificial intelligence and surgical robotics, with a primary focus on deep learning for surgical instrument recognition and segmentation. Her seminal systematic review, "Deep learning for surgical instrument recognition and segmentation in robotic-assisted surgeries," has garnered 35 citations since its 2024 publication, establishing her as a key voice in this rapidly evolving field. In this comprehensive work, Ahmed analyzed 48 studies employing advanced deep learning architectures, synthesizing critical insights into how AI can enhance annotation and tracking of surgical tools during robot-assisted minimally invasive surgeries. Her contributions are particularly significant for improving surgical precision, safety, and autonomous robotic assistance. By mapping the landscape of DL methods—from convolutional neural networks to transformer-based models—she has provided a foundational resource for researchers and clinicians alike. Ahmed’s work not only advances technical understanding but also bridges the gap between computational innovation and clinical application, positioning her as a pivotal figure in the future of intelligent surgical systems.
Research Focus
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Top Papers
- 1