Ryan Hakim
Papers
3
Total Citations
21
H-Index
3
About
Ryan Hakim is a researcher at the intersection of urology, robotic surgery, and artificial intelligence, with a focus on enhancing surgical precision and training. His work investigates how technical skills in robot-assisted surgery—particularly suturing—impact procedural success, and how external factors like the COVID-19 pandemic can degrade surgical performance. In a highly cited 2020 study in the *Journal of Endourology*, Hakim and colleagues demonstrated that urologists' robotic surgical efficiency and accuracy measurably decayed during the pandemic shutdown, a finding with direct implications for surgical readiness and training protocols. He has also pioneered the use of deep learning-based computer vision to automatically recognize and classify suturing gestures, a contribution that has garnered early citations for its potential to automate skill assessment. Further dissecting surgical technique, his 2021 work showed that proficiency in specific suturing substeps—such as needle positioning and driving—directly influences overall task success. With over 20 citations across his most prominent papers, Hakim’s research is shaping how the field measures, maintains, and improves robotic surgical skill, blending clinical urology with cutting-edge computational methods.
Research Focus
Key Achievements
Top Papers
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