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Understanding Robotic Thyroid Surgery Using AI Video Analysis

Automated Surgical Workflow Analysis of Robotic Thyroidectomy Using an AI-Based Spatio-Temporal Framework

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
CRIS
Registry ID
KCT0011205
Enrollment
200
Registered
2025-11-24
Start date
2025-11-17
Completion date
Unknown
Last updated
2025-12-08

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None listed

Interventions

None listed

Sponsors

Seoul National University Bundang Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Patients who underwent robotic right thyroid lobectomy

Exclusion criteria

Exclusion criteria: video corruption, incomplete recording, or non-standard surgical procedures (e.g., modified radical neck dissection, completion thyroidectomy).

Design outcomes

Primary

MeasureTime frame
performance of the AI model, measured by precision, recall, and F1-score—

Secondary

MeasureTime frame
Performance of the spatio-temporal analysis framework that combines surgical instrument recognition and surgical phase recognition, including instrument detection accuracy (mAP, precision, recall) and the performance gain of the integrated model over phase-only models (differences in accuracy and F1-score).—

Countries

Korea, Republic of

Contacts

Public ContactHyeong Won Yu

Seoul National University Bundang Hospital

hyeongwonyu@gmail.com+82-31-787-7099

Outcome results

None listed

Source: CRIS (via WHO ICTRP) · Data processed: Feb 4, 2026