AI; Evidence synthesis; Foundation models; Generative AI; LLM; ML; NLP; Sports Medicine; Orthopedics and Sports Medicine
Résumé :
[en] In an era of electronical medical records, rapidly expanding publication rates of medical knowledge, and large-scale registries, orthopaedics is in a dire need of innovative approaches to facilitate the adoption of the latest knowledge in clinical practice. While machine learning (ML) has been heralded as one solution to many research tasks hampered by previous technological limitations [12], there is an increasing need to direct our attention towards subdomains of ML that are convenient for the extraction of meaningful clinical information stored in medical records. We believe natural language processing (NLP) to be one such domain of ML, with an immense future potential to catalyse rate-limiting steps in orthopaedic research.
Zsidai, Bálint ; Sahlgrenska Sports Medicine Center, Gothenburg, Sweden. balint.zsidai@gu.se ; Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. balint.zsidai@gu.se
Kaarre, Janina; Sahlgrenska Sports Medicine Center, Gothenburg, Sweden ; Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden ; Department of Orthopaedic Surgery, UPMC Freddie Fu Sports Medicine Center, University of Pittsburgh, Pittsburgh, USA
Hilkert, Ann-Sophie; Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden ; Medfield Diagnostics AB, Gothenburg, Sweden
Narup, Eric; Sahlgrenska Sports Medicine Center, Gothenburg, Sweden ; Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
Senorski, Eric Hamrin; Sahlgrenska Sports Medicine Center, Gothenburg, Sweden ; Department of Health and Rehabilitation, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden ; Sportrehab Sports Medicine Clinic, Gothenburg, Sweden
Ayeni, Olufemi R; Division of Orthopaedic Surgery, Department of Surgery, McMaster University, Hamilton, Canada
Musahl, Volker; Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden ; Department of Orthopaedic Surgery, UPMC Freddie Fu Sports Medicine Center, University of Pittsburgh, Pittsburgh, USA
LEY, Christophe ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Mathematics (DMATH)
Herbst, Elmar; Department of Trauma, Hand and Reconstructive Surgery, University Hospital Münster, Münster, Germany
Hirschmann, Michael T; Department of Orthopedic Surgery and Traumatology, Head Knee Surgery and DKF Head of Research, Kantonsspital Baselland, 4101, Bruderholz, Bottmingen, Switzerland
Kopf, Sebastian; Center of Orthopaedics and Traumatology, University Hospital Brandenburg a.d.H., Brandenburg Medical School Theodor Fontane, 14770, Brandenburg, Germany ; Faculty of Health Sciences Brandenburg, Brandenburg Medical School Theodor Fontane, 14770, Brandenburg, Germany
Seil, Romain; Department of Orthopaedic Surgery, Centre Hospitalier Luxembourg and Luxembourg Institute of Health, Luxembourg, Luxembourg
Tischer, Thomas; Clinic for Orthopaedics and Trauma Surgery, Malteser Waldkrankenhaus St. Marien, Erlangen, Germany
Samuelsson, Kristian; Sahlgrenska Sports Medicine Center, Gothenburg, Sweden ; Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden ; Department of Orthopaedics, Sahlgrenska University Hospital, Mölndal, Sweden
Feldt, Robert; Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden
Eckhardt CM, Madjarova SJ, Williams RJ, Ollivier M, Karlsson J, Pareek A et al (2023) Unsupervised machine learning methods and emerging applications in healthcare. Knee Surg Sports Traumatol Arthrosc 31:376–381 DOI: 10.1007/s00167-022-07233-7
Jin D, Szolovits P (2020) Advancing PICO element detection in biomedical text via deep neural networks. Bioinformatics 36:3856–3862 DOI: 10.1093/bioinformatics/btaa256
Karhade AV, Bongers MER, Groot OQ, Kazarian ER, Cha TD, Fogel HA et al (2020) Natural language processing for automated detection of incidental durotomy. Spine J 20:695–700 DOI: 10.1016/j.spinee.2019.12.006
Langerhuizen DWG, Brown LE, Doornberg JN, Ring D, Kerkhoffs G, Janssen SJ (2021) Analysis of online reviews of orthopaedic surgeons and orthopaedic practices using natural language processing. J Am Acad Orthop Surg 29:337–344 DOI: 10.5435/JAAOS-D-20-00288
Mesko B, Topol EJ (2023) The imperative for regulatory oversight of large language models (or generative AI) in healthcare. NPJ Digit Med 6:120 DOI: 10.1038/s41746-023-00873-0
Moor M, Banerjee O, Abad ZSH, Krumholz HM, Leskovec J, Topol EJ et al (2023) Foundation models for generalist medical artificial intelligence. Nature 616:259–265 DOI: 10.1038/s41586-023-05881-4
Northcutt CG, Athalye A, Mueller J (2021) Pervasive label errors in test sets destabilize machine learning benchmarks. arXiv preprint arXiv:2103.14749
Pruneski JA, Pareek A, Kunze KN, Martin RK, Karlsson J, Oeding JF et al (2023) Supervised machine learning and associated algorithms: applications in orthopedic surgery. Knee Surg Sports Traumatol Arthrosc 31(4):1196–1202 DOI: 10.1007/s00167-022-07181-2
Pruneski JA, Pareek A, Nwachukwu BU, Martin RK, Kelly BT, Karlsson J et al (2023) Natural language processing: using artificial intelligence to understand human language in orthopedics. Knee Surg Sports Traumatol Arthrosc 31(4):1203–1211 DOI: 10.1007/s00167-022-07272-0
Rädsch T, Reinke A, Weru V, Tizabi MD, Schreck N, Kavur AE et al (2023) Labelling instructions matter in biomedical image analysis. Nat Mach Intell 5:273–283 DOI: 10.1038/s42256-023-00625-5
Rubinger L, Gazendam A, Ekhtiari S, Bhandari M (2023) Machine learning and artificial intelligence in research and healthcare. Injury 54(Suppl 3):S69–S73 DOI: 10.1016/j.injury.2022.01.046
Shiner B, Levis M, Dufort VM, Patterson OV, Watts BV, DuVall SL et al (2022) Improvements to PTSD quality metrics with natural language processing. J Eval Clin Pract 28:520–530 DOI: 10.1111/jep.13587
Singhal K, Tu T, Gottweis J, Sayres R, Wulczyn E, Hou L, et al. (2023) Towards expert-level medical question answering with large language models. arXiv preprint arXiv:2305.09617
Wyles CC, Tibbo ME, Fu S, Wang Y, Sohn S, Kremers WK et al (2019) Use of natural language processing algorithms to identify common data elements in operative notes for total hip arthroplasty. J Bone Joint Surg Am 101:1931–1938 DOI: 10.2106/JBJS.19.00071
Yang X, Chen A, PourNejatian N, Shin HC, Smith KE, Parisien C et al (2022) A large language model for electronic health records. NPJ Digit Med 5:194 DOI: 10.1038/s41746-022-00742-2
Zhu E, Sheng Q, Yang H, Li J (2022) A Unified Framework of Medical Information Annotation and Extraction for Chinese Clinical Text. arXiv preprint arXiv:2203.03823
Zsidai B, Kaarre J, Hamrin Senorski E, Feldt R, Grassi A, Ayeni OR, et al. (2022) Living evidence: a new approach to the appraisal of rapidly evolving musculoskeletal research. Br J Sports Med. 10.1136/bjsports-2022-105570
