A practical guide to the implementation of AI in orthopaedic research, Part 6: How to evaluate the performance of AI research?
Review article, 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
Author
Felix C. Oettl
Hospital for Special Surgery
Schulthess Klinik
Ayoosh Pareek
Hospital for Special Surgery
Philipp W. Winkler
Johannes Kepler University of Linz (JKU)
University of Gothenburg
Sahlgrenska University Hospital
Bálint Zsidai
University of Gothenburg
Sahlgrenska University Hospital
James Pruneski
Tripler Army Medical Center
Eric Hamrin Senorski
Sahlgrenska University Hospital
University of Gothenburg
Sebastian Kopf
Medizinische Hochschule Brandenburg Theodor Fontane
Christophe Ley
University of Luxembourg
Elmar Herbst
Division of General Internal Medicine
Jacob F. Oeding
University of Gothenburg
Mayo Clinic
Alberto Grassi
IRCCS Istituto Ortopedico Rizzoli, Bologna
Michael T. Hirschmann
University of Basel
Canton Hospital Basel-Land
Volker Musahl
University of Pittsburgh
Kristian Samuelsson
University of Gothenburg
Sahlgrenska University Hospital
Thomas Tischer
Malteser Waldkrankenhaus Erlangen
University of Rostock
Robert Feldt
Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers)
Journal of Experimental Orthopaedics
2197-1153 (eISSN)
Vol. 11 3 e12039Subject Categories (SSIF 2011)
Social Sciences Interdisciplinary
DOI
10.1002/jeo2.12039