혈액암 인자 유효성 검증과 분류를 위한 진단 예측 알고리즘 성능 비교 분석

Other Titles
Comparative Analysis of Diagnostic Prediction Algorithm Performance for Blood Cancer Factor Validation and Classification
Authors
Jeong Jae-Seung주현수조치현
Issue Date
2022-10
Publisher
한국멀티미디어학회
Citation
멀티미디어학회논문지, v.25, no.10, pp.1512 - 1523
Abstract
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.
Keywords
Artificial Intelligence; Digital Health Care; Machine Learning; Diagnostic Prediction Learning; Classifier
ISSN
1229-7771
URI
https://pubs.kist.re.kr/handle/201004/114454
DOI
10.9717/kmms.2022.25.10.1512
Appears in Collections:
KIST Article > 2022
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