Cargando…
Multitask learning and benchmarking with clinical time series data
Health care is one of the most exciting frontiers in data mining and machine learning. Successful adoption of electronic health records (EHRs) created an explosion in digital clinical data available for analysis, but progress in machine learning for healthcare research has been difficult to measure...
Autores principales: | Harutyunyan, Hrayr, Khachatrian, Hrant, Kale, David C., Ver Steeg, Greg, Galstyan, Aram |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6572845/ https://www.ncbi.nlm.nih.gov/pubmed/31209213 http://dx.doi.org/10.1038/s41597-019-0103-9 |
Ejemplares similares
-
Understanding Confounding Effects in Linguistic Coordination: An Information-Theoretic Approach
por: Gao, Shuyang, et al.
Publicado: (2015) -
Discovering Higher-Order Interactions Through Neural Information Decomposition
por: Reing, Kyle, et al.
Publicado: (2021) -
Identifying geopolitical event precursors using attention-based LSTMs
por: Hossain, K. S. M. Tozammel, et al.
Publicado: (2022) -
Benchmarking atlas-level data integration in single-cell genomics
por: Luecken, Malte D., et al.
Publicado: (2021) -
The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data
por: Ding, Daisy Yi, et al.
Publicado: (2019)