Temporal self-attention for risk prediction from electronic health records using non-stationary kernel approximation-Reference-Cited by-同舟云学术

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Temporal self-attention for risk prediction from electronic health records using non-stationary kernel approximation

Published:2024-03 Issue: Volume:149 Page:102802
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

AlSaad Rawan^ORCID,Malluhi Qutaibah^ORCID,Abd-alrazaq Alaa^ORCID,Boughorbel Sabri^ORCID

Funder

Sidra Medicine

Publisher

Elsevier BV

Reference48 articles.

1. Clinical study applying machine learning to detect a rare disease: results and lessons learned;Hersh;JAMIA Open,2022

2. Performance and usability testing of an automated tool for detection of peripheral artery disease using electronic health records;Ghanzouri;Sci Rep,2022

3. A deep learning based automatic severity detector for diabetic retinopathy;AlSaad,2018

4. Scalable and accurate deep learning with electronic health records;Rajkomar;npj Digit Med,2018

5. PredictPTB: an interpretable preterm birth prediction model using attention-based recurrent neural networks;AlSaad;BioData Min,2022

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