Jeong Jae-Seung 주현수 조치현 2024-01-19T11:01:26Z 2024-01-19T11:01:26Z 2022-11-10 2022-10 1229-7771 https://pubs.kist.re.kr/handle/201004/114454 Artificial intelligence application in digital health care has been increasing with its development of artificial intelligence. The convergence of the healthcare industry and information and communication technology makes the diagnosis of diseases more simple and comprehensible. From the perspective of medical services, its practice as an initial test and a reference indicator may become widely applicable. Therefore, analyzing the factors that are the basis for existing diagnosis protocols also helps suggest directions using artificial intelligence beyond previous regression and statistical analyses. This paper conducts essential diagnostic prediction learning based on the analysis of blood cancer factors reported previously. Blood cancer diagnosis predictions based on artificial intelligence contribute to successfully achieve more than 90% accuracy and validation of blood cancer factors as an alternative auxiliary approach. Korean 한국멀티미디어학회 혈액암 인자 유효성 검증과 분류를 위한 진단 예측 알고리즘 성능 비교 분석 Comparative Analysis of Diagnostic Prediction Algorithm Performance for Blood Cancer Factor Validation and Classification Article 10.9717/kmms.2022.25.10.1512 2 멀티미디어학회논문지, v.25, no.10, pp.1512 - 1523 멀티미디어학회논문지 25 10 1512 1523 N kci ART002892179 Artificial Intelligence Digital Health Care Machine Learning Diagnostic Prediction Learning Classifier