This paper is in the following e-collection/theme issue:

Adoption and Change Management of eHealth Systems (743) Artificial Intelligence (1480) Machine Learning (1535) New and Emerging Methods and Tools in Surgery and Anaesthesiology (44)

Published on in Vol 8, No 5 (2020): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17647, first published .
Clinical Desire for an Artificial Intelligence–Based Surgical Assistant System: Electronic Survey–Based Study

Clinical Desire for an Artificial Intelligence–Based Surgical Assistant System: Electronic Survey–Based Study

Clinical Desire for an Artificial Intelligence–Based Surgical Assistant System: Electronic Survey–Based Study

Authors of this article:

Soo Jin Park1 Author Orcid Image ;   Eun Ji Lee1 Author Orcid Image ;   Se Ik Kim1 Author Orcid Image ;   Seong-Ho Kong2 Author Orcid Image ;   Chang Wook Jeong3 Author Orcid Image ;   Hee Seung Kim1 Author Orcid Image
Article Authors Cited by (6) Tweetations (1) Metrics

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  2. Laudanski K. Quo Vadis Anesthesiologist? The Value Proposition of Future Anesthesiologists Lies in Preserving or Restoring Presurgical Health after Surgical Insult. Journal of Clinical Medicine 2022;11(4):1135 View
  3. Lünse S, Wisotzky E, Beckmann S, Paasch C, Hunger R, Mantke R. Technological advancements in surgical laparoscopy considering artificial intelligence: a survey among surgeons in Germany. Langenbeck's Archives of Surgery 2023;408(1) View
  4. Nabeel A, Al-Sabah S, Al-Ghanim K, Al-Roumi D, Al-Basri D, Ziyab A, Ashrafian H. Assessing and evaluating the impact of operative vision compromise (OViC) on surgeons’ practice: a qualitative study. International Journal of Surgery 2024;110(11):6972 View
  5. Kocielnik R, Yang C, Ma R, Cen S, Wong E, Chu T, Knudsen J, Wager P, Heard J, Ghaffar U, Anandkumar A, Hung A. Human AI collaboration for unsupervised categorization of live surgical feedback. npj Digital Medicine 2024;7(1) View