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Machine learning for risk stratification of diabetic foot ulcers using biomarkers.

Martin, Kyle; Upadhyay, Ashish; Wijekoon, Anjana; Wiratunga, Nirmalie; Massie, Stewart

Authors

Anjana Wijekoon



Contributors

Jifi Mikyška
Editor

Clélia de Mulatier
Editor

Maciej Paszynski
Editor

Valeria V. Krzhizhanovskaya
Editor

Jack J. Dongarra
Editor

Peter M.A. Sloot
Editor

Abstract

Development of a Diabetic Foot Ulcer (DFU) causes a sharp decline in a patient's health and quality of life. The process of risk stratification is crucial for informing the care that a patient should receive to help manage their Diabetes before an ulcer can form. In existing practice, risk stratification is a manual process where a clinician allocates a risk category based on biomarker features captured during routine appointments. We present the preliminary outcomes of a feasibility study on machine learning techniques for risk stratification of DFU formation. Our findings highlight the importance of considering patient history, and allow us to identify biomarkers which are important for risk classification.

Citation

MARTIN, K., UPADHYAY, A., WIJEKOON, A., WIRATUNGA, N. and MASSIE, S. 2023. Machine learning for risk stratification of diabetic foot ulcers using biomarkers. In Mikyška, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational science: proceedings of the 23rd International conference on computational science 2023 (ICCS 2023): computing at the cutting edge of science (ICCS 2023), 3-5 July 2023, Prague, Czech Republic: [virtual event]. Lecture notes in computer science, 14075. Cham: Springer [online], part III, pages 153-161. Available from: https://doi.org/10.1007/978-3-031-36024-4_11

Presentation Conference Type Conference Paper (published)
Conference Name International conference on computational science 2023 (ICCS 2023): computing at the cutting edge of science
Start Date Jul 3, 2023
End Date Jul 5, 2023
Acceptance Date Apr 4, 2023
Online Publication Date Jun 26, 2023
Publication Date Dec 31, 2023
Deposit Date Apr 25, 2023
Publicly Available Date Jun 27, 2024
Publisher Springer
Peer Reviewed Peer Reviewed
Volume Part III
Pages 153-161
Series Title Lecture notes in computer science (LNCS)
Series Number 14075
Series ISSN 0302-9743; 1611-3349
Book Title Computational science
ISBN 9783031360237
DOI https://doi.org/10.1007/978-3-031-36024-4_11
Keywords Diabetic foot ulceration; Machine learning; Biomarkers
Public URL https://rgu-repository.worktribe.com/output/1937818

Files

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Copyright Statement
This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-36024-4_11 . Use of this Accepted Version is subject to the publisher's Accepted Manuscript terms of use: https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms






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