Establishment of the World's First Telerobotic Remote Surgical Service
Bibliographic record
Abstract
In Brief Objective: To establish a telerobotic surgical service between a teaching hospital and a rural hospital for provision of telerobotic surgery and assistance to aid rural surgeons in providing a variety of advanced laparoscopic surgery to their community patients. Summary Background Data: The above service was established between St. Joseph's Hospital in Hamilton and North Bay General Hospital 400 km north of Hamilton on February 28, 2003. The service uses an IP-VPN (15 Mbps of bandwidth) commercially available network to connect the robotic console in Hamilton with 3 arms of the Zeus-TS surgical system in North Bay. Results: To date, 21 telerobotic laparoscopic surgeries have taken place between North Bay and Hamilton, including 13 fundoplications, 3 sigmoid resections, 2 right hemicolectomies, 1 anterior resection, and 2 inguinal hernia repairs. The 2 surgeons were able to operate together using the same surgical footprint and interchange roles seamlessly when desired. There have been no serious intraoperative complications and no cases have had to be converted to open surgeries. The mean hospital stays were equivalent to mean laparoscopic LOS in the tertiary institution. Conclusions: Telerobotic remote surgery is now in routine use, providing high-quality laparoscopic surgical services to patients in a rural community and providing a superior degree of collaboration between surgeons in teaching hospitals and rural hospitals. Further refinement of the robotic and telecommunication technology should ensure its wider application in the near future. We report the establishment of the world's first clinical telerobotic remote surgical service between a teaching hospital in Hamilton, Ontario and a rural community hospital in North Bay, Ontario, how the service was established, and a brief report of our experience with the first 21 telerobotic remote advanced laparoscopic procedures performed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".