An interpretable risk prediction model for healthcare with pattern attention

BACKGROUND: The availability of massive amount of data enables the possibility of clinical predictive tasks. Deep learning methods have achieved promising performance on the tasks. However, most existing methods suffer from three limitations: (1) There are lots of missing value for real value events...

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Detalles Bibliográficos
Autores principales: Kamal, Sundreen Asad, Yin, Changchang, Qian, Buyue, Zhang, Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7772928/
https://www.ncbi.nlm.nih.gov/pubmed/33380322
http://dx.doi.org/10.1186/s12911-020-01331-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7772928/
https://www.ncbi.nlm.nih.gov/pubmed/33380322
http://dx.doi.org/10.1186/s12911-020-01331-7

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