This paper investigates the use of such methods on a real dataset, and confronts its results to ones obtained with more traditional methods of longitudinal data ...
Feb 9, 2018 · This paper investigates the application of the advanced modelling techniques provided by the deep learning framework in the analysis of the longitudinal data.
Sep 8, 2024 · Conclusion: Deep artificial neural networks can be used to visualize longitudinal data in a low dimensional manifold that is much simpler to ...
Jan 12, 2024 · Deep representation learning for clustering longitudinal survival data from electronic health records · Find this author on Google Scholar ...
This paper investigates the application of the advanced modelling techniques provided by the deep learning framework in the analysis of the longitudinal ...
Feb 6, 2024 · Clustering in longitudinal data, and more specifically in short time series, involves grouping entities based on the similarity of their trajectories over time.
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Oct 10, 2022 · In the present study, several unsupervised techniques are employed to cluster patients based on longitudinal recovery profiles.
Aug 5, 2023 · This paper provides a comprehensive and critical review of recent developments and applications in machine learning for longitudinal biomedical data.
Mar 19, 2023 · A clustering algorithm being able to work with multiple rows of observations belonging to the same participant. Especially if the amount of rows varies per ...
We consider the problem of predictive modeling from irreg- ularly and sparsely sampled longitudinal data with unknown, complex correlation structures and ...