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






Felix C. Oettl

Hospital for Special Surgery - New York

Schulthess Klinik

Ayoosh Pareek

Hospital for Special Surgery - New York

Philipp W. Winkler

Sahlgrenska universitetssjukhuset

Johannes Kepler Universität Linz (JKU)

Göteborgs universitet

Bálint Zsidai

Göteborgs universitet

Sahlgrenska universitetssjukhuset

James Pruneski

Tripler Regional Med 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

Mayo Clinic Alix School of Medicine

Göteborgs universitet

Alberto Grassi

IRCCS Istituto Ortopedico Rizzoli, Bologna

Michael T. Hirschmann

Kantonsspital Baselland

Universität Basel

Volker Musahl

UPMC Sports Medicine

Kristian Samuelsson

Göteborgs universitet

Sahlgrenska universitetssjukhuset

Thomas Tischer

Malteser Waldkrankenhaus Erlangen

Universitymedicine Rostock

Robert Feldt

Chalmers, Data- och informationsteknik, Software Engineering

Journal of Experimental Orthopaedics

2197-1153 (eISSN)

Vol. 11 3 e12039


Tvärvetenskapliga studier



Mer information

Senast uppdaterat