Development of an ontology for laparoscopic transabdominal adrenalectomy via a comprehensive modified Delphi survey and its validation on a multicentric pilot data set for surgical training and future video analysis with machine learning algorithms

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	British Journal of Surgery Jg. 111
Hauptverfasser:	Barbara Seeliger, Sofia Di Lorenzo, Pier F Alesina, Laurent Brunaud, Costanza Chiapponi, Carmela De Crea, Gianluca Donatini, Maurizio Iacobone, Özer Makay, Radu Mihai, Martina T Mogl, Didier Mutter, Nicolas Padoy, Fausto Palazzo, Oscar Vidal, Francesco Pennestrí, Jacques Marescaux, Michel Vix, Marco Raffaelli
Format:	Journal Article
Sprache:	Japanisch
Veröffentlicht:	Oxford University Press (OUP) 01.06.2024
Schlagworte:	[INFO.EIAH]Computer Science [cs]/Technology for Human Learning [INFO.INFO-IM]Computer Science [cs]/Medical Imaging [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] [SDV.MHEP.CHI]Life Sciences [q-bio]/Human health and pathology/Surgery [SDV.MHEP.HEG]Life Sciences [q-bio]/Human health and pathology/Hépatology and Gastroenterology MESH: Adrenalectomy / education MESH: Adrenalectomy / methods MESH: Delphi Technique MESH: Humans MESH: Laparoscopy / education MESH: Laparoscopy / methods MESH: Machine Learning MESH: Pilot Projects MESH: Video Recording Research Letter
ISSN:	0007-1323, 1365-2168
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Beschreibung
ISSN:	0007-1323 1365-2168
DOI:	10.1093/bjs/znae148