Identifying time patterns in Huntington’s disease trajectories using dynamic time warping-based clustering on multi-modal data

Identifying time patterns in Huntington’s disease trajectories using dynamic time warping-based clustering on multi-modal data

Abstract One of the principal goals of Precision Medicine is to stratify patients by accounting for individual variability. However, extracting meaningful information from Real-World Data, such as Electronic Health Records, still remains challenging due to methodological and computational issues. A...

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Bibliographic Details
Main Authors: Alexia Giannoula, Audrey E. De Paepe, Ferran Sanz, Laura I. Furlong, Estela Camara
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Precision medicine
Longitudinal cohort analysis
Multi-modal Real-World Data
Patient stratification
Unsupervised clustering
Time analysis
Online Access:https://doi.org/10.1038/s41598-025-86686-5
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