A practical guide to the implementation of AI in orthopaedic research, Part 6: How to evaluate the performance of AI research?
Reviewartikel, 2024
Artificial intelligence's (AI) accelerating progress demands rigorous evaluation standards to ensure safe, effective integration into healthcare's high-stakes decisions. As AI increasingly enables prediction, analysis and judgement capabilities relevant to medicine, proper evaluation and interpretation are indispensable. Erroneous AI could endanger patients; thus, developing, validating and deploying medical AI demands adhering to strict, transparent standards centred on safety, ethics and responsible oversight. Core considerations include assessing performance on diverse real-world data, collaborating with domain experts, confirming model reliability and limitations, and advancing interpretability. Thoughtful selection of evaluation metrics suited to the clinical context along with testing on diverse data sets representing different populations improves generalisability. Partnering software engineers, data scientists and medical practitioners ground assessment in real needs. Journals must uphold reporting standards matching AI's societal impacts. With rigorous, holistic evaluation frameworks, AI can progress towards expanding healthcare access and quality. Level of Evidence: Level V.
performance metrics
digitalization
AI
ML
healthcare
Författare
Felix C. Oettl
Hospital for Special Surgery
Schulthess Klinik
Ayoosh Pareek
Hospital for Special Surgery
Philipp W. Winkler
Johannes Kepler Universität Linz (JKU)
Göteborgs universitet
Sahlgrenska universitetssjukhuset
Bálint Zsidai
Göteborgs universitet
Sahlgrenska universitetssjukhuset
James Pruneski
Tripler Army Medical Center
Eric Hamrin Senorski
Sahlgrenska universitetssjukhuset
Göteborgs universitet
Sebastian Kopf
Medizinische Hochschule Brandenburg Theodor Fontane
Christophe Ley
Université du Luxembourg
Elmar Herbst
Division of General Internal Medicine
Jacob F. Oeding
Göteborgs universitet
Mayo Clinic
Alberto Grassi
IRCCS Istituto Ortopedico Rizzoli, Bologna
Michael T. Hirschmann
Universität Basel
Kantonsspital Baselland
Volker Musahl
University of Pittsburgh
Kristian Samuelsson
Göteborgs universitet
Sahlgrenska universitetssjukhuset
Thomas Tischer
Malteser Waldkrankenhaus Erlangen
Universität Rostock
Robert Feldt
Chalmers, Data- och informationsteknik, Software Engineering
Journal of Experimental Orthopaedics
2197-1153 (eISSN)
Vol. 11 3 e12039Ämneskategorier (SSIF 2011)
Tvärvetenskapliga studier
DOI
10.1002/jeo2.12039