Visualization of incrementally learned projection trajectories for longitudinal data.
In: Scientific reports, Jg. 14 (2024-06-12), Heft 1, S. 13558
Online
academicJournal
Zugriff:
Longitudinal studies that continuously generate data enable the capture of temporal variations in experimentally observed parameters, facilitating the interpretation of results in a time-aware manner. We propose IL-VIS (incrementally learned visualizer), a new machine learning pipeline that incrementally learns and visualizes a progression trajectory representing the longitudinal changes in longitudinal studies. At each sampling time point in an experiment, IL-VIS generates a snapshot of the longitudinal process on the data observed thus far, a new feature that is beyond the reach of classical static models. We first verify the utility and correctness of IL-VIS using simulated data, for which the true progression trajectories are known. We find that it accurately captures and visualizes the trends and (dis)similarities between high-dimensional progression trajectories. We then apply IL-VIS to longitudinal multi-electrode array data from brain cortical organoids when exposed to different levels of quinolinic acid, a metabolite contributing to many neuroinflammatory diseases including Alzheimer's disease, and its blocking antibody. We uncover valuable insights into the organoids' electrophysiological maturation and response patterns over time under these conditions.
(© 2024. The Author(s).)
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Visualization of incrementally learned projection trajectories for longitudinal data.
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Autor/in / Beteiligte Person: | Malepathirana, T ; Senanayake, D ; Gautam, V ; Engel, M ; Balez, R ; Lovelace, MD ; Sundaram, G ; Heng, B ; Chow, S ; Marquis, C ; Guillemin, GJ ; Brew, B ; Jagadish, C ; Ooi, L ; Halgamuge, S |
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Zeitschrift: | Scientific reports, Jg. 14 (2024-06-12), Heft 1, S. 13558 |
Veröffentlichung: | London : Nature Publishing Group, copyright 2011-, 2024 |
Medientyp: | academicJournal |
ISSN: | 2045-2322 (electronic) |
DOI: | 10.1038/s41598-024-63511-z |
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