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A versatile computational algorithm for time-series data analysis and machine-learning models

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Authors: Taylor Chomiak, Neilen P. Rasiah, Leonardo A. Molina, Bin Hu, Jaideep S. Bains & Tamás Füzesi
Publication: npj Parkinson's Disease 
Date: November 9, 2021
Link to article: https://doi.org/10.1038/s41531-021-00240-4


Here we introduce Local Topological Recurrence Analysis (LoTRA), a simple computational approach for analyzing time-series data. Its versatility is elucidated using simulated data, Parkinsonian gait, and in vivo brain dynamics. We also show that this algorithm can be used to build a remarkably simple machine-learning model capable of outperforming deep-learning models in detecting Parkinson’s disease from a single digital handwriting test.

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