A self-knowledge distillation-driven CNN-LSTM model for predicting disease outcomes using longitudinal microbiome data

MOTIVATION: Human microbiome is complex and highly dynamic in nature. Dynamic patterns of the microbiome can capture more information than single point inference as it contains the temporal changes information. However, dynamic information of the human microbiome can be hard to be captured due to th...

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Detalles Bibliográficos
Autores principales: Fung, Daryl L X, Li, Xu, Leung, Carson K, Hu, Pingzhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10203376/
https://www.ncbi.nlm.nih.gov/pubmed/37228387
http://dx.doi.org/10.1093/bioadv/vbad059

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10203376/
https://www.ncbi.nlm.nih.gov/pubmed/37228387
http://dx.doi.org/10.1093/bioadv/vbad059

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