{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T20:23:23Z","timestamp":1790713403530,"version":"4.1.0"},"reference-count":130,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T00:00:00Z","timestamp":1768435200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Hand Surg Eur Vol"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:sec>\n                    <jats:title>Introduction:<\/jats:title>\n                    <jats:p>Artificial intelligence (AI) is becoming increasingly integrated into clinical care in hand surgery. Its applications extend across diagnosis, planning, intraoperative assistance, postoperative monitoring, rehabilitation, prosthetics and education.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Applications:<\/jats:title>\n                    <jats:p>In diagnostic imaging, AI improves the detection of distal radius and scaphoid fractures, estimates osteoporosis from hand radiographs, identifies triangular fibrocartilage complex injuries on magnetic resonance imaging, segments bones and cartilage, and supports dynamic wrist analysis; ultrasound- and neurophysiological-based models aid carpal tunnel syndrome diagnosis. Prognostic models predict outcomes after carpal tunnel release and thumb carpometacarpal osteoarthritis with mixed performance. Pre- and intraoperative applications include large language model-based triage and coding, navigation and phase\/gesture recognition from surgical video, autonomous microsurgical prototypes and telemanipulator platforms for supermicrosurgery. Artificial intelligence-enabled telemonitoring (e.g. remote photoplethysmography) and video-based mobility tracking support postoperative care and rehabilitation. Vision-guided and multimodal sensing enhance myoelectric prosthesis control.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Risks:<\/jats:title>\n                    <jats:p>Risks include data privacy and security, algorithmic bias (data, transposition, normative, annotation) and opacity, overreliance with automation bias and skill erosion, and unresolved legal and ethical questions (liability, conflicts of interest, compassion in care).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>Balanced adoption requires diversified datasets, privacy-preserving strategies (pseudonymization, differential privacy, federated learning), transparent reporting, AI literacy and ethics in medical education and interfaces that expose uncertainty and employ cognitive forcing functions. Post-deployment surveillance should track data drift, out-of-distribution inputs and performance using automated alerts and multidisciplinary review. Artificial intelligence should augment, never replace, clinical judgment, with explicit role delineation and continuous monitoring to safeguard equity and patient-centred outcomes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/17531934251401382","type":"journal-article","created":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T07:07:08Z","timestamp":1768547228000},"page":"685-697","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["The balance between artificial and human intelligence in clinical practice"],"prefix":"10.1177","volume":"51","author":[{"given":"Domenico","family":"Marrella","sequence":"first","affiliation":[{"name":"Department of Hand Surgery, Strasbourg University Hospitals, FMTS, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Turkka","family":"Anttila","sequence":"additional","affiliation":[{"name":"Department of Musculoskeletal and Plastic Surgery, Meilahti, Bridge-hospital, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jorma","family":"Ryh\u00e4nen","sequence":"additional","affiliation":[{"name":"Department of Musculoskeletal and Plastic Surgery, Meilahti, Bridge-hospital, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7090-2710","authenticated-orcid":false,"given":"Robert","family":"Miller","sequence":"additional","affiliation":[{"name":"Plastic and Reconstructive Surgery Department, Guy\u2019s and St Thomas\u2019 NHS Foundation Trust, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Hand Surgery, Beijing Jishuitan Hospital, Capital Medical University and Fourth Clinical College of Peking University and Beijing Jishuitan Hospital, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5509-8995","authenticated-orcid":false,"given":"Philippe","family":"Liverneaux","sequence":"additional","affiliation":[{"name":"Department of Hand Surgery, Strasbourg University Hospitals, FMTS, France"},{"name":"ICube CNRS UMR7357, Strasbourg University, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,1,15]]},"reference":[{"key":"e_1_3_2_2_1","article-title":"A systematic review of the barriers to the implementation of artificial intelligence in healthcare","volume":"15","author":"Ahmed MI","year":"2023","unstructured":"Ahmed MI, Spooner B, Isherwood J, Lane M, Orrock E, Dennison A. A systematic review of the barriers to the implementation of artificial intelligence in healthcare. Cureus. 2023, 15: e46454.","journal-title":"Cureus"},{"key":"e_1_3_2_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0094-1298(20)31576-5"},{"key":"e_1_3_2_4_1","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2024.1336588"},{"key":"e_1_3_2_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/MLSP.2018.8517005"},{"key":"e_1_3_2_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-022-26647-4"},{"key":"e_1_3_2_7_1","article-title":"Quality of ChatGPT responses to frequently asked questions in carpal tunnel release surgery","volume":"12","author":"Amen TB","year":"2024","unstructured":"Amen TB, Torabian KA, Subramanian T, Yang BW, Liimakka A, Fufa D. Quality of ChatGPT responses to frequently asked questions in carpal tunnel release surgery. Plast Reconstr Surg Glob Open. 2024, 12: e5822.","journal-title":"Plast Reconstr Surg Glob Open"},{"key":"e_1_3_2_8_1","doi-asserted-by":"publisher","DOI":"10.3390\/jcm12227129"},{"key":"e_1_3_2_9_1","article-title":"Detecting distal radius fractures using a segmentation-based deep learning model","volume":"36","author":"Anttila TT","year":"2023","unstructured":"Anttila TT, Karjalainen TV, M\u00e4kel\u00e4 TO, et al. Detecting distal radius fractures using a segmentation-based deep learning model. J Digit Imaging. 2023b, 36: 679\u201387.","journal-title":"J Digit Imaging"},{"key":"e_1_3_2_10_1","doi-asserted-by":"publisher","DOI":"10.3390\/bioengineering11020175"},{"key":"e_1_3_2_11_1","first-page":"671","article-title":"Big data\u2019s disparate impact","volume":"104","author":"Barocas S","year":"2016","unstructured":"Barocas S, Selbst AD. Big data\u2019s disparate impact. Calif Law Rev. 2016, 104: 671.","journal-title":"Calif Law Rev"},{"key":"e_1_3_2_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-023-02939-6"},{"key":"e_1_3_2_13_1","article-title":"Physiotherapie f\u00fcr die Hosentasche: Effektivit\u00e4t von Heim\u00fcbungen mittels KI-basierter Smartphone App zur Nachbehandlung von Handverletzungen \u2013 eine randomisierte, kontrollierte und offene Studie","volume":"57","author":"Bauknecht S","year":"2025","unstructured":"Bauknecht S, Moeller R, Mentzel M, Lebelt M, Mack J, Vergote D. Physiotherapie f\u00fcr die Hosentasche: Effektivit\u00e4t von Heim\u00fcbungen mittels KI-basierter Smartphone App zur Nachbehandlung von Handverletzungen \u2013 eine randomisierte, kontrollierte und offene Studie. Handchir Mikrochir Plast Chir. 2025, 57: 186\u201394.","journal-title":"Handchir Mikrochir Plast Chir"},{"key":"e_1_3_2_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jid.2023.10.004"},{"key":"e_1_3_2_15_1","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.4320"},{"key":"e_1_3_2_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3449287"},{"key":"e_1_3_2_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhsa.2023.08.009"},{"key":"e_1_3_2_18_1","article-title":"The boundaries of privacy harm","volume":"86","author":"Calo R.","year":"2011","unstructured":"Calo R. The boundaries of privacy harm. Indiana Law J. 2011, 86: 1131\u201358.","journal-title":"Indiana Law J"},{"key":"e_1_3_2_19_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnbot.2014.00022"},{"key":"e_1_3_2_20_1","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2023.1305756"},{"key":"e_1_3_2_21_1","article-title":"Artificial intelligence powered advancements in upper extremity joint MRI: a review","volume":"10","author":"Chen W","year":"2024","unstructured":"Chen W, Lim LJR, Lim RQR, et al. Artificial intelligence powered advancements in upper extremity joint MRI: a review. Heliyon. 2024a, 10: e28731.","journal-title":"Heliyon"},{"key":"e_1_3_2_22_1","doi-asserted-by":"publisher","DOI":"10.3389\/fbioe.2024.1420100"},{"key":"e_1_3_2_23_1","doi-asserted-by":"publisher","DOI":"10.2196\/53616"},{"key":"e_1_3_2_24_1","doi-asserted-by":"publisher","DOI":"10.1377\/hlthaff.2014.0048"},{"key":"e_1_3_2_25_1","first-page":"93","article-title":"Big data and due process: toward a framework to redress predictive privacy harms","volume":"55","author":"Crawford K","year":"2014","unstructured":"Crawford K, Schultz J. Big data and due process: toward a framework to redress predictive privacy harms. BCL Rev. 2014, 55: 93\u2013128.","journal-title":"BCL Rev"},{"key":"e_1_3_2_26_1","doi-asserted-by":"publisher","DOI":"10.1177\/15589447241247332"},{"key":"e_1_3_2_27_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pdig.0000651"},{"key":"e_1_3_2_28_1","unstructured":"Dawson D. Schleiger E. Horton J. et al. (2019). Artificial intelligence: Australia\u2019s ethics framework \u2013 a discussion paper. Analysis & Policy Observatory. Canberra: CSIRO Data61. https:\/\/apo.org.au\/node\/229596 (Accessed: 26 November 2025)."},{"key":"e_1_3_2_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2016.7590732"},{"key":"e_1_3_2_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2023.3311628"},{"key":"e_1_3_2_31_1","doi-asserted-by":"publisher","DOI":"10.1177\/17531934241258868"},{"key":"e_1_3_2_32_1","unstructured":"Health Edge. (2024). Evaluating pathways for AI dermatology in skin cancer detection: a white paper. NHSE Outpatient Recovery and Transformation Programme. https:\/\/www.edgehealth.co.uk\/wp-content\/uploads\/2024\/08\/Evaluating-Pathways-for-AI-Dermatology-in-Skin-Cancer-Detection.pdf (Accessed: 26 November 2025)."},{"key":"e_1_3_2_33_1","doi-asserted-by":"publisher","DOI":"10.1159\/000353435"},{"key":"e_1_3_2_34_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature21056"},{"key":"e_1_3_2_35_1","unstructured":"Exer AI. (2024 March). Exer AI collaborates with Mayo Clinic to advance standard of care for hand and wrist disorders with AI. https:\/\/www.exer.ai\/news\/exer-ai-collaborates-with-mayo-clinic (Accessed: 24 March 2025)."},{"key":"e_1_3_2_36_1","doi-asserted-by":"publisher","DOI":"10.1002\/hast.134"},{"key":"e_1_3_2_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2017.12.003"},{"key":"e_1_3_2_38_1","doi-asserted-by":"publisher","DOI":"10.1111\/os.13957"},{"key":"e_1_3_2_39_1","doi-asserted-by":"publisher","DOI":"10.1097\/SLA.0000000000004425"},{"key":"e_1_3_2_40_1","first-page":"433","article-title":"Health AI for good rather than evil? The need for a new regulatory framework for AI-based medical devices","volume":"20","author":"Gerke S.","year":"2021","unstructured":"Gerke S. Health AI for good rather than evil? The need for a new regulatory framework for AI-based medical devices. Yale J Health Policy Law Ethics. 2021, 20: 433\u2013513.","journal-title":"Yale J Health Policy Law Ethics"},{"key":"e_1_3_2_41_1","doi-asserted-by":"publisher","DOI":"10.1136\/amiajnl-2011-000089"},{"key":"e_1_3_2_42_1","article-title":"Analyzing surgical technique in diverse open surgical videos with a multi-task real-time AI model capable of quantifying kinematic hand motion descriptors that distinguish surgeon skill levels","volume":"159","author":"Goodman ED","year":"2024","unstructured":"Goodman ED, Patel KK, Zhang Y, et al. Analyzing surgical technique in diverse open surgical videos with a multi-task real-time AI model capable of quantifying kinematic hand motion descriptors that distinguish surgeon skill levels. JAMA Surg. 2024, 159: e230626.","journal-title":"JAMA Surg"},{"key":"e_1_3_2_43_1","doi-asserted-by":"publisher","DOI":"10.1080\/15265161.2015.1062162"},{"key":"e_1_3_2_44_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.otsr.2023.103564"},{"key":"e_1_3_2_45_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2025.110995"},{"key":"e_1_3_2_46_1","doi-asserted-by":"publisher","DOI":"10.2196\/35587"},{"key":"e_1_3_2_47_1","doi-asserted-by":"publisher","DOI":"10.3389\/fneur.2022.1052505"},{"key":"e_1_3_2_48_1","article-title":"Developing machine learning algorithms to support patient-centered, value-based carpal tunnel decompression surgery","volume":"11","author":"Harrison CJ","year":"2023","unstructured":"Harrison CJ, Geoghegan L, Sidey-Gibbons CJ, Stirling PHC, McEachan JE, Rodrigues JN. Developing machine learning algorithms to support patient-centered, value-based carpal tunnel decompression surgery. Plast Reconstr Surg Glob Open. 2023, 11: e4744.","journal-title":"Plast Reconstr Surg Glob Open"},{"key":"e_1_3_2_49_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jham.2025.100258"},{"key":"e_1_3_2_50_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-025-01503-7"},{"key":"e_1_3_2_51_1","doi-asserted-by":"publisher","DOI":"10.1097\/SLA.0000000000002693"},{"key":"e_1_3_2_52_1","doi-asserted-by":"publisher","DOI":"10.2196\/48633"},{"key":"e_1_3_2_53_1","unstructured":"Haworth J. Biswas R. Opfermann J. et al. (2024 October 10). Autonomous robotic system with optical coherence tomography guidance for vascular anastomosis. arXiv preprint arXiv:2410.07493 [cs.RO] v1. https:\/\/arxiv.org\/abs\/2410.07493"},{"key":"e_1_3_2_54_1","doi-asserted-by":"publisher","DOI":"10.1097\/PRS.0000000000010108"},{"key":"e_1_3_2_55_1","article-title":"Artificial intelligence in surgical coding: evaluating large language models for current procedural terminology accuracy in hand surgery","volume":"7","author":"Isch EL","year":"2025","unstructured":"Isch EL, Lee J, Self DM, et al. Artificial intelligence in surgical coding: evaluating large language models for current procedural terminology accuracy in hand surgery. J Hand Surg Glob Online. 2025, 7: 181\u20135.","journal-title":"J Hand Surg Glob Online"},{"key":"e_1_3_2_56_1","doi-asserted-by":"publisher","DOI":"10.1177\/15589447241247246"},{"key":"e_1_3_2_57_1","article-title":"Advantages in precision, safety, and aesthetic outcomes of robot-assisted minimally invasive techniques in peripheral nerve microsurgery: a narrative review","volume":"2","author":"Jiang S","year":"2025","unstructured":"Jiang S, Naito K, Liverneaux P. Advantages in precision, safety, and aesthetic outcomes of robot-assisted minimally invasive techniques in peripheral nerve microsurgery: a narrative review. Adv Technol Neurosci. 2025, 2: 122\u20137.","journal-title":"Adv Technol Neurosci"},{"key":"e_1_3_2_58_1","doi-asserted-by":"publisher","DOI":"10.5152\/j.aott.2022.21310"},{"key":"e_1_3_2_59_1","first-page":"4596","volume-title":"In Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society","author":"Juarez-Villalobos L.","year":"2021","unstructured":"Juarez-Villalobos L., Hevia-Montiel N., Perez-Gonzalez J., (2021). Machine learning\u2013based classification of local robotic surgical skills in a training tasks set. In Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 4596\u20134599). Virtual conference, hosted from Guadalajara, Mexico, November 1\u20135, 2021."},{"key":"e_1_3_2_60_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0094-1298(20)31578-9"},{"key":"e_1_3_2_61_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10459-021-10040-3"},{"key":"e_1_3_2_62_1","doi-asserted-by":"publisher","DOI":"10.1038\/ejhg.2014.71"},{"key":"e_1_3_2_63_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-023-02831-3"},{"key":"e_1_3_2_64_1","doi-asserted-by":"publisher","DOI":"10.1080\/15265161.2022.2075056"},{"key":"e_1_3_2_65_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11701-024-01867-0"},{"key":"e_1_3_2_66_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-022-00737-z"},{"key":"e_1_3_2_67_1","article-title":"Artificial intelligence for X-ray scaphoid fracture detection: a systematic review and diagnostic test accuracy meta-analysis","volume":"34","author":"Kraus M","year":"2024","unstructured":"Kraus M, Anteby R, Konen E, Eshed I, Klang E. Artificial intelligence for X-ray scaphoid fracture detection: a systematic review and diagnostic test accuracy meta-analysis. Eur Radiol. 2024, 34: 4341\u201351.","journal-title":"Eur Radiol"},{"key":"e_1_3_2_68_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12938-020-00768-1"},{"key":"e_1_3_2_69_1","doi-asserted-by":"publisher","DOI":"10.1097\/CORR.0000000000001318"},{"key":"e_1_3_2_70_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2017170236"},{"key":"e_1_3_2_71_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj-2024-081554"},{"key":"e_1_3_2_72_1","doi-asserted-by":"publisher","DOI":"10.1177\/17531934251326153"},{"key":"e_1_3_2_73_1","doi-asserted-by":"publisher","DOI":"10.3390\/jpm12071029"},{"key":"e_1_3_2_74_1","doi-asserted-by":"publisher","DOI":"10.1177\/1753193419848595"},{"key":"e_1_3_2_75_1","doi-asserted-by":"publisher","DOI":"10.1177\/1753193419841253"},{"key":"e_1_3_2_76_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-020-1034-x"},{"key":"e_1_3_2_77_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.main.2005.06.004"},{"key":"e_1_3_2_78_1","article-title":"Feasibility of wrist arthroscopy using a new free hand camera robot-assisted prototype","volume":"1","author":"Liverneaux P","year":"2016","unstructured":"Liverneaux P, Pruni\u00e8res G, Hidalgo Diaz JJ, Salazar Botero S, Vernet P, Facca S. Feasibility of wrist arthroscopy using a new free hand camera robot-assisted prototype. Mathews J Orthop. 2016, 1: 010.","journal-title":"Mathews J Orthop"},{"key":"e_1_3_2_79_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.obhdp.2018.12.005"},{"key":"e_1_3_2_80_1","article-title":"Machine learning can be used to predict function but not pain after surgery for thumb carpometacarpal osteoarthritis","volume":"480","author":"Loos NL","year":"2022","unstructured":"Loos NL, Hoogendam L, Souer JS, et al. Machine learning can be used to predict function but not pain after surgery for thumb carpometacarpal osteoarthritis. Clin Orthop Relat Res. 2022, 480: 1271\u201384.","journal-title":"Clin Orthop Relat Res"},{"key":"e_1_3_2_81_1","doi-asserted-by":"publisher","DOI":"10.1227\/neu.0000000000002848"},{"key":"e_1_3_2_82_1","doi-asserted-by":"publisher","DOI":"10.1097\/SCS.0000000000011150"},{"key":"e_1_3_2_83_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.hansur.2024.101742"},{"key":"e_1_3_2_84_1","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/12\/6\/066022"},{"key":"e_1_3_2_85_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.hansur.2025.102225"},{"key":"e_1_3_2_86_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2024.e26297"},{"key":"e_1_3_2_87_1","doi-asserted-by":"publisher","DOI":"10.1177\/17531934231152592"},{"key":"e_1_3_2_88_1","doi-asserted-by":"publisher","DOI":"10.1177\/17531934241312896"},{"key":"e_1_3_2_89_1","doi-asserted-by":"publisher","DOI":"10.1177\/17531934251342418"},{"key":"e_1_3_2_90_1","article-title":"Leveraging large language models (LLM) for the plastic surgery resident training: do they have a role?","volume":"56","author":"Mohapatra DP","year":"2023","unstructured":"Mohapatra DP, Thiruvoth FM, Tripathy S, et al. Leveraging large language models (LLM) for the plastic surgery resident training: do they have a role? Indian J Plast Surg. 2023, 56: 413\u201320.","journal-title":"Indian J Plast Surg"},{"key":"e_1_3_2_91_1","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2022.971044"},{"key":"e_1_3_2_92_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0305949"},{"key":"e_1_3_2_93_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhsa.2024.01.020"},{"key":"e_1_3_2_94_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-025-03626-6"},{"key":"e_1_3_2_95_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.hansur.2024.101717"},{"key":"e_1_3_2_96_1","article-title":"Machine learning-based approach for disease severity classification of carpal tunnel syndrome","volume":"11","author":"Park D","year":"2021","unstructured":"Park D, Kim BH, Lee SE, et al. Machine learning-based approach for disease severity classification of carpal tunnel syndrome. Sci Rep. 2021, 11: 17464.","journal-title":"Sci Rep"},{"key":"e_1_3_2_97_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultrasmedbio.2023.10.009"},{"key":"e_1_3_2_98_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.hansur.2024.101723"},{"key":"e_1_3_2_99_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.hansur.2024.102073"},{"key":"e_1_3_2_100_1","doi-asserted-by":"publisher","DOI":"10.3390\/jcm13102832"},{"key":"e_1_3_2_101_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-018-0272-7"},{"key":"e_1_3_2_102_1","doi-asserted-by":"publisher","DOI":"10.4337\/9781802205657.00016"},{"key":"e_1_3_2_103_1","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocaa268"},{"key":"e_1_3_2_104_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics11061077"},{"key":"e_1_3_2_105_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-020-00323-1"},{"key":"e_1_3_2_106_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhsa.2020.04.021"},{"key":"e_1_3_2_107_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-658-47422-5_27"},{"key":"e_1_3_2_108_1","doi-asserted-by":"publisher","DOI":"10.1177\/17531934251322723"},{"key":"e_1_3_2_109_1","doi-asserted-by":"publisher","DOI":"10.1259\/bjr.20220878"},{"key":"e_1_3_2_110_1","doi-asserted-by":"publisher","DOI":"10.1093\/eurpub\/ckae144.1125"},{"key":"e_1_3_2_111_1","doi-asserted-by":"publisher","DOI":"10.1055\/s-0034-1368161"},{"key":"e_1_3_2_112_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.arthro.2022.03.037"},{"key":"e_1_3_2_113_1","doi-asserted-by":"publisher","DOI":"10.5812\/jme-137753"},{"key":"e_1_3_2_114_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacr.2025.06.036"},{"key":"e_1_3_2_115_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00701-024-05896-4"},{"key":"e_1_3_2_116_1","doi-asserted-by":"publisher","DOI":"10.1177\/1753193420968399"},{"key":"e_1_3_2_117_1","doi-asserted-by":"publisher","DOI":"10.2196\/46020"},{"key":"e_1_3_2_118_1","doi-asserted-by":"publisher","DOI":"10.1177\/17531934231209876"},{"key":"e_1_3_2_119_1","first-page":"3511","volume-title":"In Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society","author":"Trachtenberg M. S.","year":"2011","unstructured":"Trachtenberg M. S., Singhal G., Kaliki R., Smith R. J., Thakor N. V., (2011). Radio frequency identification \u2013 an innovative solution to guide dexterous prosthetic hands. In Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 3511\u20133514). Boston, Massachusetts, USA, August 30\u2013September 3, 2011."},{"key":"e_1_3_2_120_1","doi-asserted-by":"publisher","DOI":"10.3390\/bioengineering8110181"},{"key":"e_1_3_2_121_1","unstructured":"US Food and Drug Administration. (2023). Methods and tools for effective postmarket monitoring of artificial intelligence (AI)-enabled medical devices. https:\/\/www.fda.gov\/medical-devices\/medical-device-regulatory-science-research-programs-conducted-osel\/methods-and-tools-effective-postmarket-monitoring-artificial-intelligence-ai-enabled-medical-devices (Accessed: 26 November 2025)."},{"key":"e_1_3_2_122_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jrt.2025.100108"},{"key":"e_1_3_2_123_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-14188-w"},{"key":"e_1_3_2_124_1","doi-asserted-by":"publisher","DOI":"10.1145\/3579605"},{"key":"e_1_3_2_125_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-023-02835-z"},{"key":"e_1_3_2_126_1","article-title":"Reimagining medical education in the age of AI","volume":"21","author":"Wartman SA","year":"2019","unstructured":"Wartman SA, Combs CD. Reimagining medical education in the age of AI. AMA J Ethics. 2019, 21: E146\u201352.","journal-title":"AMA J Ethics"},{"key":"e_1_3_2_127_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnbot.2022.815716"},{"key":"e_1_3_2_128_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-023-00964-0"},{"key":"e_1_3_2_129_1","doi-asserted-by":"publisher","DOI":"10.2106\/JBJS.RVW.24.00106"},{"key":"e_1_3_2_130_1","doi-asserted-by":"publisher","DOI":"10.1111\/os.13677"},{"key":"e_1_3_2_131_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-024-01212-9"}],"container-title":["Journal of Hand Surgery (European Volume)"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/17531934251401382","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/17531934251401382","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/17531934251401382","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T05:48:50Z","timestamp":1780033730000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/17531934251401382"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,15]]},"references-count":130,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["10.1177\/17531934251401382"],"URL":"https:\/\/doi.org\/10.1177\/17531934251401382","relation":{},"ISSN":["1753-1934","2043-6289"],"issn-type":[{"value":"1753-1934","type":"print"},{"value":"2043-6289","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,15]]}}}