Scalable Causal Structure Learning: Scoping Review of Traditional and Deep Learning Algorithms and New Opportunities in Biomedicine
BackgroundCausal structure learning refers to a process of identifying causal structures from observational data, and it can have multiple applications in biomedicine and health care. ObjectiveThis paper provides a practical review and tutorial on scalable causal...
Main Authors: | Pulakesh Upadhyaya, Kai Zhang, Can Li, Xiaoqian Jiang, Yejin Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
JMIR Publications
2023-01-01
|
Series: | JMIR Medical Informatics |
Online Access: | https://medinform.jmir.org/2023/1/e38266 |
Similar Items
-
Deep Learning and Machine Learning Applications in Biomedicine
by: Peiyi Yan, et al.
Published: (2023-12-01) -
Deep Learning and Its Applications in Biomedicine
by: Chensi Cao, et al.
Published: (2018-02-01) -
Graphene Oxide: Opportunities and Challenges in Biomedicine
by: Pariya Zare, et al.
Published: (2021-04-01) -
Special Issue: Deep Learning and Neuro-Evolution Methods in Biomedicine and Bioinformatics
by: Mauro Castelli
Published: (2022-08-01) -
Scalable deep learning for watershed model calibration
by: Maruti K. Mudunuru, et al.
Published: (2022-11-01)