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http://dx.doi.org/10.9708/jksci.2022.27.12.069

Method of preventing Pressure Ulcer and EMR data preprocess  

Kim, Dowon (Dept. of Computer Science and Engineering, Kangwon National University)
Kim, Minkyu (Dept. of Research and Development, ZIOVISION Co. Ltd)
Kim, Yoon (Dept. of Computer Science and Engineering, Kangwon National University)
Han, Seon-Sook (Dept. of Internal Medicine, Kangwon National University Hospital)
Heo, Jungwon (Dept. of Internal Medicine, Kangwon National University Hospital)
Choi, Hyun-Soo (Dept. of Computer Science and Engineering, Kangwon National University, Dept. of Computer Science and Engineering, Seoul National University of Science and Technology)
Publication Information
Journal of the Korea Society of Computer and Information / v.27, no.12, 2022 , pp. 69-76 More about this Journal
Abstract
This paper proposes a method of refining and processing time-series data using Medical Information Mart for Intensive Care (MIMIC-IV) v2.0 data. In addition, the significance of the processing method was validated through a machine learning-based pressure ulcer early warning system using a dataset processed based on the proposed method. The implemented system alerts medical staff in advance 12 and 24 hours before a lesion occurs. In conjunction with the Electronic Medical Record (EMR) system, it informs the medical staff of the risk of a patient's pressure ulcer development in real-time to support a clinical decision, and further, it enables the efficient allocation of medical resources. Among several machine learning models, the GRU model showed the best performance with AUROC of 0.831 for 12 hours and 0.822 for 24 hours.
Keywords
Pressure Ulcer; Time-series; EMR; Deep Learning;
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Times Cited By KSCI : 2  (Citation Analysis)
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