Dynamic Modeling of Patient Vital Signs: Leveraging Markov Chain Principles with Neural Networks for Irregular Time-Series Prediction-Reference-Cited by-同舟云学术

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Dynamic Modeling of Patient Vital Signs: Leveraging Markov Chain Principles with Neural Networks for Irregular Time-Series Prediction

Published:2024-06-30 Issue: Volume:56 Page:1-8
ISSN:
Container-title:2024 International Joint Conference on Neural Networks (IJCNN)
language:
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Author:

Choy Xin Yun¹,Rong Wang Li¹,Henderson Thomas C.²,Li Kelvin³,Ng Yih Yng⁴,Fan Xiuyi⁵

Affiliation:

1. Nanyang Technological University,School of Computer Science and Engineering,Singapore,Singapore

2. University of Utah,School of Computing,Salt Lake City,USA

3. Tan Tock Seng Hospital,Department of Ophthalmology,Singapore,Singapore

4. Centre of Healthcare Innovation,Digital and Smart Health Office,Singapore,Singapore

5. Nanyang Technological University,Lee Kong Chian School of Medicine,Singapore,Singapore

Funder

Ministry of Education

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10649807/10649898/10650842.pdf?arnumber=10650842

Reference37 articles.

1. The Factors that Affect the Frequency of Vital Sign Monitoring in the Emergency Department

2. Vital signs monitoring to detect patient deterioration: An integrative literature review

3. Rapid-Response Systems as a Patient Safety Strategy

4. Remote patient monitoring using artificial intelligence: Current state, applications, and challenges

5. An intelligent warning model for early prediction of cardiac arrest in sepsis patients

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