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Emergency Department Return Prediction System Using Blood Samples With LightGBM for Smart Health Care Services

Authors
 Younghwan Shin  ;  Sangdo Kim  ;  Jong-Moon Chung  ;  Hyun Soo Chung  ;  Sang Gil Han  ;  Junho Cho 
Citation
 IEEE CONSUMER ELECTRONICS MAGAZINE, Vol.10(3) : 42-48, 2020-11 
Journal Title
 IEEE CONSUMER ELECTRONICS MAGAZINE 
ISSN
 2162-2248 
Issue Date
2020-11
Keywords
Blood ; Hospitals ; Smart healthcare ; Decision trees ; Emergency services ; Medical services ; Internet of Things
Abstract
This article proposes a novel Blood sample-based Emergency department (ED) Return (BER) scheme that predicts the ED return probability using LightGBM. In the proposed BER scheme, LightGBM makes predictions on ED return based on blood samples. Since blood sample analysis is one of the most common medical procedures, the proposed scheme can help to improve ED patient care for hospitals. The proposed BER smart health care system and internet of medical things (IoMT) blockchain network was tested from the ED of the Severance Hospital of Yonsei University, located in Seoul of South Korea. The results show that the proposed BER scheme is superior in predicting ED return visits based on achieving a higher Area Under the Curve of the Receiver Operating Characteristic performance, along with the advantage of using much lesser data and being faster.
Full Text
https://ieeexplore.ieee.org/document/9165157
DOI
10.1109/MCE.2020.3015439
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Emergency Medicine (응급의학교실) > 1. Journal Papers
Yonsei Authors
Chung, Hyun Soo(정현수) ORCID logo https://orcid.org/0000-0001-6110-1495
Cho, Junho(조준호) ORCID logo https://orcid.org/0000-0003-2240-3989
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/182833
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