{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T12:42:42Z","timestamp":1793882562184,"version":"4.7.0"},"reference-count":32,"publisher":"Elsevier BV","issue":"8","license":[{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"vor","delay-in-days":366,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Orthopaedics &amp; Traumatology: Surgery &amp; Research"],"published-print":{"date-parts":[[2023,12]]},"DOI":"10.1016\/j.otsr.2023.103652","type":"journal-article","created":{"date-parts":[[2023,6,26]],"date-time":"2023-06-26T16:04:47Z","timestamp":1687795487000},"page":"103652","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":13,"special_numbering":"S","title":["Can artificial intelligence help decision-making in arthroscopy? Part 2: The IA-RTRHO model\u00a0\u2013\u00a0a decision-making aid for long head of the biceps diagnoses in small rotator cuff tears"],"prefix":"10.1016","volume":"109","author":[{"given":"Rayane","family":"Benhenneda","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thierry","family":"Brouard","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christophe","family":"Charousset","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julien","family":"Berhouet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.otsr.2023.103652_bib0165","first-page":"10","article-title":"Artificial intelligence in modern orthopaedics: current and future applications","author":"Hui","year":"2022","journal-title":"JBJS Rev"},{"key":"10.1016\/j.otsr.2023.103652_bib0170","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"key":"10.1016\/j.otsr.2023.103652_bib0175","doi-asserted-by":"crossref","first-page":"840282","DOI":"10.3389\/frobt.2022.840282","article-title":"Artificial intelligence based patient-specific preoperative planning algorithm for total knee arthroplasty","volume":"9","author":"Lambrechts","year":"2022","journal-title":"Front Robot AI"},{"key":"10.1016\/j.otsr.2023.103652_bib0180","doi-asserted-by":"crossref","first-page":"2535","DOI":"10.1007\/s00167-022-07035-x","article-title":"Artificial intelligence and robotics in TKA surgery: promising options for improved outcomes?","volume":"30","author":"von Eisenhart-Rothe","year":"2022","journal-title":"Knee Surg Sports Traumatol Arthrosc"},{"key":"10.1016\/j.otsr.2023.103652_bib0185","doi-asserted-by":"crossref","first-page":"e225","DOI":"10.1016\/j.jse.2020.07.042","article-title":"Using machine learning to predict clinical outcomes after shoulder arthroplasty with a minimal feature set","volume":"30","author":"Kumar","year":"2021","journal-title":"J Shoulder Elbow Surg"},{"key":"10.1016\/j.otsr.2023.103652_bib0190","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1002\/ags3.12513","article-title":"Artificial intelligence-based computer vision in surgery: recent advances and future perspectives","volume":"6","author":"Kitaguchi","year":"2022","journal-title":"Ann Gastroenterol Surg"},{"key":"10.1016\/j.otsr.2023.103652_bib0195","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1016\/j.arthro.2014.02.021","article-title":"The knee arthroscopy learning curve: quantitative assessment of surgical skills","volume":"30","author":"Hodgins","year":"2014","journal-title":"Arthroscopy"},{"key":"10.1016\/j.otsr.2023.103652_bib0200","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1007\/s00167-021-06554-3","article-title":"The Diagnostic Arthroscopy Skill Score (DASS): a reliable and suitable assessment tool for arthroscopic skill training","volume":"30","author":"Anetzberger","year":"2022","journal-title":"Knee Surg Sports Traumatol Arthrosc"},{"key":"10.1016\/j.otsr.2023.103652_bib0205","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1007\/s00167-015-3947-3","article-title":"History of shoulder instability surgery","volume":"24","author":"Randelli","year":"2016","journal-title":"Knee Surg Sports Traumatol Arthrosc"},{"key":"10.1016\/j.otsr.2023.103652_bib0210","doi-asserted-by":"crossref","first-page":"3229","DOI":"10.1007\/s00167-015-3862-7","article-title":"Physical examination tests and imaging studies based on arthroscopic assessment of the long head of biceps tendon are invalid","volume":"25","author":"Jordan","year":"2017","journal-title":"Knee Surg Sports Traumatol Arthrosc"},{"key":"10.1016\/j.otsr.2023.103652_bib0215","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.jse.2004.07.008","article-title":"Arthroscopic tenotomy of the long head of the biceps in the treatment of rotator cuff tears: clinical and radiographic results of 307 cases","volume":"14","author":"Walch","year":"2005","journal-title":"J Shoulder Elbow Surg"},{"key":"10.1016\/j.otsr.2023.103652_bib0220","doi-asserted-by":"crossref","first-page":"951","DOI":"10.1016\/j.jse.2020.11.012","article-title":"Biceps tenodesis versus tenotomy: a systematic review and meta-analysis of level I randomized controlled trials","volume":"30","author":"Belk","year":"2021","journal-title":"J Shoulder Elbow Surg"},{"key":"10.1016\/j.otsr.2023.103652_bib0225","doi-asserted-by":"crossref","first-page":"1439","DOI":"10.1177\/0363546520912212","article-title":"Biceps tenodesis versus tenotomy in the treatment of lesions of the long head of the biceps tendon in patients undergoing arthroscopic shoulder surgery: a prospective double-blinded randomized controlled trial","volume":"48","author":"MacDonald","year":"2020","journal-title":"Am J Sports Med"},{"key":"10.1016\/j.otsr.2023.103652_bib0230","doi-asserted-by":"crossref","first-page":"1939","DOI":"10.1016\/j.jse.2018.03.030","article-title":"Tenodesis renders better results than tenotomy in repairs of isolated supraspinatus tears with pathologic biceps","volume":"27","author":"Goden\u00e8che","year":"2018","journal-title":"J Shoulder Elbow Surg"},{"key":"10.1016\/j.otsr.2023.103652_bib0235","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/s00167-017-4609-4","article-title":"Tenodesis is not superior to tenotomy in the treatment of the long head of biceps tendon lesions","volume":"26","author":"Castricini","year":"2018","journal-title":"Knee Surg Sports Traumatol Arthrosc"},{"key":"10.1016\/j.otsr.2023.103652_bib0240","series-title":"StatPearls","author":"Doyle","year":"2021"},{"key":"10.1016\/j.otsr.2023.103652_bib0245","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1016\/j.jclinepi.2004.10.018","article-title":"The development of a comorbidity index with physical function as the outcome","volume":"58","author":"Groll","year":"2005","journal-title":"J Clin Epidemiol"},{"key":"10.1016\/j.otsr.2023.103652_bib0250","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1097\/00003086-198701000-00023","article-title":"A clinical method of functional assessment of the shoulder","author":"Constant","year":"1987","journal-title":"Clin Orthop"},{"key":"10.1016\/j.otsr.2023.103652_bib0255","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1016\/j.jse.2007.02.123","article-title":"Comparison of the subjective shoulder value and the Constant score","volume":"16","author":"Gilbart","year":"2007","journal-title":"J Shoulder Elbow Surg"},{"key":"10.1016\/j.otsr.2023.103652_bib0260","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1016\/j.jse.2020.07.015","article-title":"The American shoulder and elbow surgeons score highly correlates with the simple shoulder test","volume":"30","author":"Baumgarten","year":"2021","journal-title":"J Shoulder Elbow Surg"},{"key":"10.1016\/j.otsr.2023.103652_bib0265","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1302\/0301-620X.95B7.31028","article-title":"Is there an association between the individual anatomy of the scapula and the development of rotator cuff tears or osteoarthritis of the glenohumeral joint?: A radiological study of the critical shoulder angle","volume":"95-B","author":"Moor","year":"2013","journal-title":"Bone J"},{"key":"10.1016\/j.otsr.2023.103652_bib0270","doi-asserted-by":"crossref","first-page":"1958","DOI":"10.1097\/CORR.0000000000000770","article-title":"Classifications in brief: bigliani classification of acromial morphology","volume":"477","author":"McLean","year":"2019","journal-title":"Clin Orthop"},{"key":"10.1016\/j.otsr.2023.103652_bib0275","doi-asserted-by":"crossref","first-page":"104115","DOI":"10.1016\/j.compbiomed.2020.104115","article-title":"A scoping review of transfer learning research on medical image analysis using ImageNet","volume":"128","author":"Morid","year":"2021","journal-title":"Comput Biol Med"},{"key":"10.1016\/j.otsr.2023.103652_bib0280","doi-asserted-by":"crossref","unstructured":"Szegedy C, Vanhoucke V, Ioffe S, Shlens J, Wojna Z. Rethinking the inception architecture for computer vision 2015. https:\/\/doi.org\/10.48550\/arXiv.1512.00567.","DOI":"10.1109\/CVPR.2016.308"},{"key":"10.1016\/j.otsr.2023.103652_bib0285","doi-asserted-by":"crossref","first-page":"102837","DOI":"10.1016\/j.otsr.2021.102837","article-title":"Deep learning for the radiographic diagnosis of proximal femur fractures: Limitations and programming issues","volume":"107","author":"Guy","year":"2021","journal-title":"Orthop Traumatol Surg Res"},{"key":"10.1016\/j.otsr.2023.103652_bib0290","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1080\/17453674.2017.1344459","article-title":"Artificial intelligence for analyzing orthopedic trauma radiographs","volume":"88","author":"Olczak","year":"2017","journal-title":"Acta Orthop"},{"key":"10.1016\/j.otsr.2023.103652_bib0295","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1111\/1754-9485.12828","article-title":"Computer vs human: deep learning versus perceptual training for the detection of neck of femur fractures","volume":"63","author":"Adams","year":"2019","journal-title":"J Med Imaging Radiat Oncol"},{"key":"10.1016\/j.otsr.2023.103652_bib0300","doi-asserted-by":"crossref","first-page":"639021","DOI":"10.1155\/2015\/639021","article-title":"Toward a literature-driven definition of big data in healthcare","volume":"2015","author":"Baro","year":"2015","journal-title":"BioMed Res Int"},{"key":"10.1016\/j.otsr.2023.103652_bib0305","doi-asserted-by":"crossref","first-page":"79","DOI":"10.4258\/hir.2013.19.2.79","article-title":"Potentiality of big data in the medical sector: focus on how to reshape the healthcare system","volume":"19","author":"Jee","year":"2013","journal-title":"Healthc Inform Res"},{"key":"10.1016\/j.otsr.2023.103652_bib0310","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1097\/SLA.0000000000001031","article-title":"Using both clinical registry and administrative claims data to measure risk-adjusted surgical outcomes","volume":"263","author":"Lawson","year":"2016","journal-title":"Ann Surg"},{"key":"10.1016\/j.otsr.2023.103652_bib0315","doi-asserted-by":"crossref","unstructured":"He K, Gkioxari G, Doll\u00e1r P, Girshick R. Mask R-CNN 2018. https:\/\/doi.org\/10.48550\/arXiv.1703.06870.","DOI":"10.1109\/ICCV.2017.322"},{"key":"10.1016\/j.otsr.2023.103652_bib0320","doi-asserted-by":"crossref","DOI":"10.1007\/s00330-022-09170-y","article-title":"Automatic segmentation of the thalamus using a massively trained 3D convolutional neural network: higher sensitivity for the detection of reduced thalamus volume by improved inter-scanner stability","author":"Opfer","year":"2022","journal-title":"Eur Radiol"}],"container-title":["Orthopaedics &amp; Traumatology: Surgery &amp; Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1877056823001433?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1877056823001433?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T03:50:33Z","timestamp":1761796233000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1877056823001433"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12]]},"references-count":32,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2023,12]]}},"alternative-id":["S1877056823001433"],"URL":"https:\/\/doi.org\/10.1016\/j.otsr.2023.103652","relation":{},"ISSN":["1877-0568"],"issn-type":[{"value":"1877-0568","type":"print"}],"subject":[],"published":{"date-parts":[[2023,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Can artificial intelligence help decision-making in arthroscopy? Part 2: The IA-RTRHO model\u00a0\u2013\u00a0a decision-making aid for long head of the biceps diagnoses in small rotator cuff tears","name":"articletitle","label":"Article Title"},{"value":"Orthopaedics & Traumatology: Surgery & Research","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.otsr.2023.103652","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2023 Elsevier Masson SAS.","name":"copyright","label":"Copyright"}],"article-number":"103652"}}