Interpretation and reporting of predictive or diagnostic machine-learning research in Trauma & Orthopaedics.

Bone Joint J · Dec 2021 · Review

Farrow L, Zhong M, Ashcroft GP, Anderson L, Meek RMD

University of Aberdeen, Aberdeen, UK

General Orthopaedics

SUMMARY — THE REDUCTIONMachine-learning models in orthopaedic surgery require clear interpretation and standardized reporting; lack of guidelines creates heterogeneity in study quality and validity.
Abstract, as published

There is increasing popularity in the use of artificial intelligence and machine-learning techniques to provide diagnostic and prognostic models for various aspects of Trauma & Orthopaedic surgery. However, correct interpretation of these models is difficult for those without specific knowledge of computing or health data science methodology. Lack of current reporting standards leads to the potential for significant heterogeneity in the design and quality of published studies. We provide an overview of machine-learning techniques for the lay individual, including key terminology and best practice reporting guidelines. Cite this article: Bone Joint J 2021;103-B(12):1754-1758.

Featured in the 2026-07-17 issue.

← Deep Learning and Multimodal Artificial Intelligence in Ortho…The Role of Amino Acid Supplementation in Orthopaedic Surgery. →

The Reduction is a free email digest of newly published orthopaedic literature — a handful of new papers in the subspecialties you choose, each summarized like this one. Subscribe free or browse the archive.