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http://dx.doi.org/10.15207/JKCS.2021.12.10.365

Analysis of Pressure Ulcer Nursing Records with Artificial Intelligence-based Natural Language Processing  

Kim, Myoung Soo (Department of Nursing, Pukyong National University)
Ryu, Jung-Mi (Department of Nursing, Busan Institute of Science and Technology)
Publication Information
Journal of the Korea Convergence Society / v.12, no.10, 2021 , pp. 365-372 More about this Journal
Abstract
The purpose of this study was to examine the statements characteristics of the pressure ulcer nursing record by natural langage processing and assess the prediction accuracy for each pressure ulcer stage. Nursing records related to pressure ulcer were analyzed using descriptive statistics, and word cloud generators (http://wordcloud.kr) were used to examine the characteristics of words in the pressure ulcer prevention nursing records. The accuracy ratio for the pressure ulcer stage was calculated using deep learning. As a result of the study, the second stage and the deep tissue injury suspected were 23.1% and 23.0%, respectively, and the most frequent key words were erythema, blisters, bark, area, and size. The stages with high prediction accuracy were in the order of stage 0, deep tissue injury suspected, and stage 2. These results suggest that it can be developed as a clinical decision support system available to practice for nurses at the pressure ulcer prevention care.
Keywords
Natural language processing; Pressure ulcer; Electronic nursing record; Classification; Nurses;
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