Automated, objective and predictive evaluation of technical skills in robot-assisted surgery

Automated, objective and predictive evaluation of technical skills in robot-assisted surgery Journal of Robotic Surgery https://doi.org/10.1007/s11701-018-0833-2 LE T TER TO  THE   EDITOR Automated, objective and predictive evaluation of technical skills in robot-assisted surgery Andrea Moglia Received: 21 March 2018 / Accepted: 3 June 2018 © Springer-Verlag London Ltd., part of Springer Nature 2018 To the Editor: experts, in accordance with published evidence reporting construct validity [4]. Although results of the study report I read with great interest the recently published article by a high accuracy on the two tasks (82.3% for knot tying and Fard et al. entitled “Automated robot-assisted surgical skill 89.9% on suture) there are some remarks. First, the study is evaluation: Predictive analytics approach.” [1]. limited to eight surgeons. More participants and exercises Trainees in robot-assisted surgery (RAS) need to acquire would be certainly useful to validate results, as discussed by different technical skills over traditional surgery because of authors [1]. Second, authors did not explain why a threshold the peculiarities of the da Vinci surgical system by Intuitive of 15 and 19 at a global rating scale was used, respectively, Surgical (Sunnyvale, CA, United States). In particular, the for knot tying and suture task, to divide surgeons between master console requires a proper level of technical skills novices and experts. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Robotic Surgery Springer Journals

Automated, objective and predictive evaluation of technical skills in robot-assisted surgery

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer-Verlag London Ltd., part of Springer Nature
Subject
Medicine & Public Health; Minimally Invasive Surgery; Surgery; Urology
ISSN
1863-2483
eISSN
1863-2491
D.O.I.
10.1007/s11701-018-0833-2
Publisher site
See Article on Publisher Site

Abstract

Journal of Robotic Surgery https://doi.org/10.1007/s11701-018-0833-2 LE T TER TO  THE   EDITOR Automated, objective and predictive evaluation of technical skills in robot-assisted surgery Andrea Moglia Received: 21 March 2018 / Accepted: 3 June 2018 © Springer-Verlag London Ltd., part of Springer Nature 2018 To the Editor: experts, in accordance with published evidence reporting construct validity [4]. Although results of the study report I read with great interest the recently published article by a high accuracy on the two tasks (82.3% for knot tying and Fard et al. entitled “Automated robot-assisted surgical skill 89.9% on suture) there are some remarks. First, the study is evaluation: Predictive analytics approach.” [1]. limited to eight surgeons. More participants and exercises Trainees in robot-assisted surgery (RAS) need to acquire would be certainly useful to validate results, as discussed by different technical skills over traditional surgery because of authors [1]. Second, authors did not explain why a threshold the peculiarities of the da Vinci surgical system by Intuitive of 15 and 19 at a global rating scale was used, respectively, Surgical (Sunnyvale, CA, United States). In particular, the for knot tying and suture task, to divide surgeons between master console requires a proper level of technical skills novices and experts.

Journal

Journal of Robotic SurgerySpringer Journals

Published: Jun 5, 2018

References

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