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Cited by in F6Publishing
For: Lam K, Chen J, Wang Z, Iqbal FM, Darzi A, Lo B, Purkayastha S, Kinross JM. Machine learning for technical skill assessment in surgery: a systematic review. NPJ Digit Med 2022;5:24. [PMID: 35241760 DOI: 10.1038/s41746-022-00566-0] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 King AJ, Kahn JM, Brant EB, Cooper GF, Mowery DL. Initial Development of an Automated Platform for Assessing Trainee Performance on Case Presentations. ATS Scholar 2022. [DOI: 10.34197/ats-scholar.2022-0010oc] [Reference Citation Analysis]
2 G. Pantelis A. Current and Potential Applications of Artificial Intelligence in Metabolic Bariatric Surgery. Bariatric Surgery - Past and Present [Working Title] 2022. [DOI: 10.5772/intechopen.106365] [Reference Citation Analysis]
3 Lam K, Abràmoff MD, Balibrea JM, Bishop SM, Brady RR, Callcut RA, Chand M, Collins JW, Diener MK, Eisenmann M, Fermont K, Neto MG, Hager GD, Hinchliffe RJ, Horgan A, Jannin P, Langerman A, Logishetty K, Mahadik A, Maier-Hein L, Antona EM, Mascagni P, Mathew RK, Müller-Stich BP, Neumuth T, Nickel F, Park A, Pellino G, Rudzicz F, Shah S, Slack M, Smith MJ, Soomro N, Speidel S, Stoyanov D, Tilney HS, Wagner M, Darzi A, Kinross JM, Purkayastha S. A Delphi consensus statement for digital surgery. NPJ Digit Med 2022;5:100. [PMID: 35854145 DOI: 10.1038/s41746-022-00641-6] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]