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

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 in a sub...

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Detalles Bibliográficos
Autores principales: Soares, Diogo F., Henriques, Rui, Gromicho, Marta, de Carvalho, Mamede, Madeira, Sara C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10105751/
https://www.ncbi.nlm.nih.gov/pubmed/37061549
http://dx.doi.org/10.1038/s41598-023-33223-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10105751/
https://www.ncbi.nlm.nih.gov/pubmed/37061549
http://dx.doi.org/10.1038/s41598-023-33223-x

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