Self-Supervised Forecasting in Electronic Health Records With Attention-Free Models-Reference-Cited by-同舟云学术

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Self-Supervised Forecasting in Electronic Health Records With Attention-Free Models

Published:2024-08 Issue:8 Volume:5 Page:3926-3938
ISSN:2691-4581
Container-title:IEEE Transactions on Artificial Intelligence
language:
Short-container-title:IEEE Trans. Artif. Intell.

Author:

Kumar Yogesh¹^ORCID,Ilin Alexander¹^ORCID,Salo Henri²^ORCID,Kulathinal Sangita³^ORCID,Leinonen Maarit K.²^ORCID,Marttinen Pekka¹^ORCID

Affiliation:

1. Department of Computer Science, Aalto University, Aalto, Finland

2. Information Services Department, Finnish Institute for Health and Welfare, Helsinki, Finland

3. Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland

Funder

Research Council of Finland

BusinessFinland

EU H2020

Research Council of Finland Flagship Program via Finnish Center for Artificial Intelligence

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9078688/10635096/10398588.pdf?arnumber=10398588

Reference69 articles.

1. Death vs. Data Science: Predicting End of Life

3. Readmission prediction using deep learning on electronic health records

4. Improving palliative care with deep learning

5. Layer normalization;Ba,2016

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Transformer models in biomedicine;BMC Medical Informatics and Decision Making;2024-07-29

2. Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker;Nature Aging;2024-06-24

3. Generating Social-Aware Locations for a Robot in a Human Group by Image Generation Using Adversarial Learning;IEEE Access;2024

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