A practical guide to the implementation of artificial intelligence in orthopaedic research-Part 2: A technical introduction.

artificial intelligence machine learning orthopaedics research methods sports medicine

Journal

Journal of experimental orthopaedics
ISSN: 2197-1153
Titre abrégé: J Exp Orthop
Pays: United States
ID NLM: 101653750

Informations de publication

Date de publication:
Jul 2024
Historique:
received: 13 12 2023
revised: 31 01 2024
accepted: 21 03 2024
medline: 8 5 2024
pubmed: 8 5 2024
entrez: 8 5 2024
Statut: epublish

Résumé

Recent advances in artificial intelligence (AI) present a broad range of possibilities in medical research. However, orthopaedic researchers aiming to participate in research projects implementing AI-based techniques require a sound understanding of the technical fundamentals of this rapidly developing field. Initial sections of this technical primer provide an overview of the general and the more detailed taxonomy of AI methods. Researchers are presented with the technical basics of the most frequently performed machine learning (ML) tasks, such as classification, regression, clustering and dimensionality reduction. Additionally, the spectrum of supervision in ML including the domains of supervised, unsupervised, semisupervised and self-supervised learning will be explored. Recent advances in neural networks (NNs) and deep learning (DL) architectures have rendered them essential tools for the analysis of complex medical data, which warrants a rudimentary technical introduction to orthopaedic researchers. Furthermore, the capability of natural language processing (NLP) to interpret patterns in human language is discussed and may offer several potential applications in medical text classification, patient sentiment analysis and clinical decision support. The technical discussion concludes with the transformative potential of generative AI and large language models (LLMs) on AI research. Consequently, this second article of the series aims to equip orthopaedic researchers with the fundamental technical knowledge required to engage in interdisciplinary collaboration in AI-driven orthopaedic research. Level IV.

Identifiants

pubmed: 38715910
doi: 10.1002/jeo2.12025
pii: JEO212025
pmc: PMC11076014
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

e12025

Informations de copyright

© 2024 The Author(s). Journal of Experimental Orthopaedics published by John Wiley & Sons Ltd on behalf of European Society of Sports Traumatology, Knee Surgery and Arthroscopy.

Déclaration de conflit d'intérêts

Michael T. Hirschmann is a consultant for Medacta, Symbios and Depuy Synthes. Kristian Samuelsson is a member on the board of directors for Getinge AB (publ). Robert Feldt is Chief Technology Officer and founder in Accelerandium AB, a software consultancy company.

Auteurs

Bálint Zsidai (B)

Sahlgrenska Sports Medicine Center Gothenburg Sweden.
Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy University of Gothenburg Gothenburg Sweden.

Janina Kaarre (J)

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.

Eric Narup (E)

Sahlgrenska Sports Medicine Center Gothenburg Sweden.
Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy University of Gothenburg Gothenburg Sweden.

Eric Hamrin Senorski (E)

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.

Ayoosh Pareek (A)

Sports and Shoulder Service, Hospital for Special Surgery New York New York USA.

Alberto Grassi (A)

Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy University of Gothenburg Gothenburg Sweden.
IIa Clinica Ortopedica e Traumatologica, IRCCS Istituto Ortopedico Rizzoli Bologna Italy.

Christophe Ley (C)

Department of Mathematics University of Luxembourg Esch-sur-Alzette Luxembourg.

Umile Giuseppe Longo (UG)

Fondazione Policlinico Universitario Campus Bio-Medico Rome Italy.
Research Unit of Orthopaedic and Trauma Surgery, Department of Medicine and Surgery Università Campus Bio-Medico di Roma Rome Italy.

Elmar Herbst (E)

Department of Trauma, Hand and Reconstructive Surgery University Hospital Münster Münster Germany.

Michael T Hirschmann (MT)

Department of Orthopedic Surgery and Traumatology, Head Knee Surgery and DKF Head of Research Kantonsspital Baselland Bruderholz Switzerland.

Sebastian Kopf (S)

Center of Orthopaedics and Traumatology University Hospital Brandenburg a.d.H., Brandenburg Medical School Theodor Fontane Brandenburg a.d.H. Germany.
Faculty of Health Sciences Brandenburg Brandenburg Medical School Theodor Fontane Brandenburg a.d.H. Germany.

Romain Seil (R)

Department of Orthopaedic Surgery Luxembourg Centre Hospitalier de Luxembourg-Clinique d'Eich Luxembourg Luxembourg.
Luxembourg Institute of Research in Orthopaedics Sports Medicine and Science (LIROMS) Luxembourg Luxembourg.
Luxembourg Institute of Health, Human Motion, Orthopaedics Sports Medicine and Digital Methods (HOSD) Luxembourg Luxembourg.

Thomas Tischer (T)

Clinic for Orthopaedics and Trauma Surgery Erlangen Germany.

Kristian Samuelsson (K)

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.

Robert Feldt (R)

Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden.

Classifications MeSH