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The Bone & Joint Journal
Vol. 104-B, Issue 9 | Pages 1011 - 1016
1 Sep 2022
Acem I van de Sande MAJ

Prediction tools are instruments which are commonly used to estimate the prognosis in oncology and facilitate clinical decision-making in a more personalized manner. Their popularity is shown by the increasing numbers of prediction tools, which have been described in the medical literature. Many of these tools have been shown to be useful in the field of soft-tissue sarcoma of the extremities (eSTS). In this annotation, we aim to provide an overview of the available prediction tools for eSTS, provide an approach for clinicians to evaluate the performance and usefulness of the available tools for their own patients, and discuss their possible applications in the management of patients with an eSTS.

Cite this article: Bone Joint J 2022;104-B(9):1011–1016.


The Bone & Joint Journal
Vol. 103-B, Issue 12 | Pages 1754 - 1758
1 Dec 2021
Farrow L Zhong M Ashcroft GP Anderson L Meek RMD

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.


The Journal of Bone & Joint Surgery British Volume
Vol. 87-B, Issue 9 | Pages 1182 - 1186
1 Sep 2005
Sher JL Reed MR Calvert P Wallace WA Lamb A