Ahmet Atik

Papers

Total Citations

H-Index

About

Ahmet Atik is a neurosurgeon and researcher at the forefront of robotic stereotactic surgery, with a focused expertise in the safe adoption and implementation of advanced cranial technologies. His work critically addresses the learning curves associated with robotic techniques for stereoelectroencephalography (sEEG) and deep brain stimulation (DBS), providing essential benchmarks for surgeons transitioning to these minimally invasive approaches. Atik’s most cited study, "Learning Curves during Implementation of Robotic Stereotactic Surgery," offers a data-driven framework for understanding the procedural volume required to achieve proficiency, directly impacting patient safety and surgical training. This foundational work, already garnering early citations, underscores his commitment to bridging the gap between technological innovation and clinical practice. By quantifying the path to mastery, Atik is helping to standardize robotic neurosurgery, making it more accessible and reproducible. His contributions are vital for the next generation of neurosurgeons, ensuring that as robotic systems become more prevalent, their integration is guided by evidence, not just enthusiasm.