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SWoTTeD: An Extension of Tensor Decomposition to Temporal Phenotyping
Feb. 21, 2024, 5:43 a.m. | Hana Sebia, Thomas Guyet, Etienne Audureau
cs.LG updates on arXiv.org arxiv.org
Abstract: Tensor decomposition has recently been gaining attention in the machine learning community for the analysis of individual traces, such as Electronic Health Records (EHR). However, this task becomes significantly more difficult when the data follows complex temporal patterns. This paper introduces the notion of a temporal phenotype as an arrangement of features over time and it proposes SWoTTeD (Sliding Window for Temporal Tensor Decomposition), a novel method to discover hidden temporal patterns. SWoTTeD integrates several …
abstract analysis arxiv attention community cs.lg data ehr electronic electronic health records extension health machine machine learning notion paper patterns records stat.ml temporal tensor traces type
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