Can Attention Be Used to Explain EHR-Based Mortality Prediction Tasks: A Case Study on Hemorrhagic Stroke-Reference-Cited by-同舟云学术

Can Attention Be Used to Explain EHR-Based Mortality Prediction Tasks: A Case Study on Hemorrhagic Stroke

Published:2023-09-03 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics
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Author:

Feng Qizhang¹^ORCID,Yuan Jiayi²^ORCID,Emdad Forhan Bin³^ORCID,Hanna Karim⁴^ORCID,Hu Xia²^ORCID,He Zhe³^ORCID

Affiliation:

1. Texas A&M University, College Station, TX, USA

2. Rice University, Houston, TX, USA

3. Florida State University, Tallahassee, FL, USA

4. University of South Florida, Tampa, FL, USA

Funder

National Center for Advancing Translational Sciences

National Library of Medicine

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3584371.3613002

Reference20 articles.

1. Yuhan Deng et al. 2022. Explainable time-series deep learning models for the prediction of mortality prolonged length of stay and 30-day readmission in intensive care patients. Frontiers in Medicine 9 (2022). Yuhan Deng et al. 2022. Explainable time-series deep learning models for the prediction of mortality prolonged length of stay and 30-day readmission in intensive care patients. Frontiers in Medicine 9 (2022).

2. Forhan Bin Emdad etal 2023. Towards A Unified Utilitarian Ethics Framework for Healthcare Artificial Intelligence. (2023). Forhan Bin Emdad et al. 2023. Towards A Unified Utilitarian Ethics Framework for Healthcare Artificial Intelligence. (2023).

3. Towards Interpretable Multimodal Predictive Models for Early Mortality Prediction of Hemorrhagic Stroke Patients;Emdad Forhan Bin;AMIA Summits on Translational Science Proceedings,2023

4. Jake Grigsby et al. 2021. Long-range transformers for dynamic spatiotemporal forecasting. arXiv preprint arXiv:2109.12218 (2021). Jake Grigsby et al. 2021. Long-range transformers for dynamic spatiotemporal forecasting. arXiv preprint arXiv:2109.12218 (2021).

5. A deep attention model to forecast the Length Of Stay and the in-hospital mortality right on admission from ICD codes and demographic data

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