Basem Ishak

Heidelberg University

Papers

2

Total Citations

31

H-Index

2

About

Basem Ishak is a leading researcher in the field of spinal neurosurgery, with a specific focus on the integration of artificial intelligence and advanced imaging to enhance surgical precision. His work centers on developing automated planning tools and validating the accuracy of navigated spinal instrumentation. Ishak’s major contributions include the creation of a convolutional neural network-based automated planning tool for lumbosacral pedicle screws, a breakthrough that streamlines preoperative planning and reduces human error. His research has been cited over 30 times, reflecting its growing influence in the surgical community. Notably, his 2022 study on CT-navigated spinal instrumentations provided a rigorous, three-dimensional evaluation of screw placement accuracy against preoperative trajectory plans, setting a new standard for quantitative assessment in the field. This work has significant implications for improving patient outcomes by minimizing screw misplacement and associated complications. Ishak’s achievements position him as a key innovator at the intersection of machine learning and spine surgery, offering practical tools that promise to enhance the safety and efficacy of complex spinal procedures.

Research Focus

Key Achievements

2
H-Index
2
Papers
31
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Development and validation of an automated planning tool for navigated lumbosacral pedicle screws using a convolutional neural network
17 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Heidelberg University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago