Is mild really mild?: Generating longitudinal profiles of stroke survivor impairment and impact using unsupervised machine learning

Authors

Achini Adikari, La Trobe University
Rashmika Nawaratne, La Trobe University
Daswin De Silva, La Trobe University
David L. Carey, La Trobe University
Alistair Walsh, La Trobe University
Carolyn Baum, Washington University School of Medicine in St. Louis
Stephen Davis, University of Melbourne
Geoffrey A. Donnan, University of Melbourne
Damminda Alahakoon, La Trobe University
Leeanne M. Carey, La Trobe University

Journal

Applied Sciences

Publication Date

8-4-2024

Volume

14

Issue

15

First Page

6800

Document Type

Open Access Publication

DOI

10.3390/app14156800

Rights and Permissions

Adikari A, Nawaratne R, De Silva, D, Carey, D.L., Walsh, A, Baum, C, Davis, S, Donnan, G.A., Alahakoon D, Carey, L.M. Is Mild Really Mild?: Generating Longitudinal Profiles of Stroke Survivor Impairment and Impact Using Unsupervised Machine Learning. Appl. Sci. 2024, 14, 6800. https://doi.org/10.3390/app14156800 Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Recommended Citation

Adikari, Achini; Nawaratne, Rashmika; De Silva, Daswin; Carey, David L.; Walsh, Alistair; Baum, Carolyn; Davis, Stephen; Donnan, Geoffrey A.; Alahakoon, Damminda; and Carey, Leeanne M., "Is mild really mild?: Generating longitudinal profiles of stroke survivor impairment and impact using unsupervised machine learning." Applied Sciences. 14, 15. 6800 (2024).
https://digitalcommons.wustl.edu/oa_4/4022

Department

ICTS (Institute of Clinical and Translational Sciences)