Quantification of Dysnatremia Using Single-Beam Acoustic Microbeam and Convolutional Neural Networks-Reference-Cited by-同舟云学术

Quantification of Dysnatremia Using Single-Beam Acoustic Microbeam and Convolutional Neural Networks

Published:2024-04-01 Issue:7 Volume:24 Page:9626-9638
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Nam Ji Won¹^ORCID,Jeon Hyeon-Ju²^ORCID,Lee Jeong Eun¹^ORCID,Lee O-Joun³^ORCID,Lim Hae Gyun¹^ORCID

Affiliation:

1. Department of Biomedical Engineering, Pukyong National University, Busan, Republic of Korea

2. Data Assimilation Group, Korea Institute of Atmospheric Prediction Systems, Seoul, Republic of Korea

3. Department of Artificial Intelligence, The Catholic University of Korea, Bucheon, Republic of Korea

Funder

National Research Foundation of Korea

Ministry of Science and ICT

Research and Development Project “Development of a Next-Generation Data Assimilation System by the Korea Institute of Atmospheric Prediction System (KIAPS),”

Korea Meteorological Administration

Pukyong National University Industry-University Cooperation Research Fund in 2023

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10487994/10439021.pdf?arnumber=10439021

Reference31 articles.

1. Characteristics, Symptoms, and Outcome of Severe Dysnatremias Present on Hospital Admission

2. Hypernatremia

3. Hyponatremia

4. Effects on the central nervous system of hypernatremic and hyponatremic states

5. Hypernatremia in Hospitalized Patients

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