Artificial intelligence-based expert trajectory guidance in an ex vivo robot-assisted renal wound suturing training model
By
Tailai Zhou
Tongyu Jia
Shangwei Li
Jiachen Zheng
Haotian Hou
Houming Zhao
Jichen Wang
Ji Feng
Xin Ma
July 2, 2026
Clinical Scorecard: AI-Driven Expert Guidance for Suturing Training in an Ex Vivo Robot-Assisted Renal Surgery Model
At a Glance
Category Detail
Condition Robot-Assisted Partial Nephrectomy Key Mechanisms Artificial intelligence framework for learning expert suturing trajectories and providing real-time visual guidance. Target Population Novice surgical trainees Care Setting Surgical training environments
Key Highlights
Development of an AI framework for expert trajectory guidance in renal wound suturing. Evaluation involved a multicenter expert trajectory dataset and a pilot training study. Novice trainees receiving AI guidance significantly outperformed unguided peers. Model achieved an average displacement error of 34.25 pixels in trajectory prediction. Study suggests potential for AI to enhance short-term skill acquisition in surgical training. Guideline-Based Recommendations
Diagnosis
Management
Monitoring & Follow-up
Risks
Patient & Prescribing Data
Not specified in the study.
AI-derived guidance may improve suturing skills in novice trainees.
Clinical Best Practices
Utilize AI frameworks for real-time guidance in complex surgical tasks. Incorporate expert trajectory data in surgical training curricula. Conduct larger multicenter randomized trials to validate findings. Related Resources & Content
