과제정보
This research was supported by the Daejeon University Research Grants (2022)
한국정보통신학회:학술대회논문집 (Proceedings of the Korean Institute of Information and Commucation Sciences Conference)
- 한국정보통신학회 2022년도 추계학술대회
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- Pages.326-327
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- 2022
머신러닝 기반 욕창 단계 분류 알고리즘
Machine Learning-based Bedscore Stage Classification Algorithm
- Cho, Young-bok (Daejeon University) ;
- Yoo, Ha-na (Daejeon University)
- 발행 : 2022.10.03
초록
본 연구는 머신러닝을 이용한 임상적 의사결정을 위한 알고리즘으로 환자를 간호하는 간호인력이 장기간 누워있는 환자를 보살힐 경우 욕창예방간호 수행에 도움을 주기 위한 시스템 개발에 활용될 욕창 분류 알고리즘이다. 머신러닝을 실시한 결과 알고리즘의 learning accuracy는 82.14%, test accuracy는 82.58%로 나타났다.
This study is an algorithm for clinical decision-making using machine learning, and it is an algorithm to classify pressure sores to be used in the development of a system to help prevent pressure sores when nursing staff care for patients who lie down for a long time. As a result of machine learning, the learning accuracy of the algorithm was 82.14% and the test accuracy was 82.58%.