Triclustering-based classification of longitudinal data for prognostic prediction: targeting relevant clinical endpoints in amyotrophic lateral sclerosis

Abstract This work proposes a new class of explainable prognostic models for longitudinal data classification using triclusters. A new temporally constrained triclustering algorithm, termed TCtriCluster, is proposed to comprehensively find informative temporal patterns common to a subset of patients...

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Bibliographic Details
Main Authors: Diogo F. Soares, Rui Henriques, Marta Gromicho, Mamede de Carvalho, Sara C. Madeira
Format: Article
Language:English
Published: Nature Portfolio 2023-04-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-33223-x