Human Normalization Approach based on Disease Comparative Prediction Model between Covid-19 and InfluenzaHuman Normalization Approach based on Disease Comparative Prediction Model between Covid-19 and Influenza
- Other Titles
- Human Normalization Approach based on Disease Comparative Prediction Model between Covid-19 and Influenza
- Authors
- 김장환; 정민용; 이다윤; 조나현; 진조아; 김영철
- Issue Date
- Aug-2023
- Publisher
- 한국인터넷방송통신학회
- Keywords
- COVID-19; Machine Learning; Traditional Korean Medicine
- Citation
- The International Journal of Internet, Broadcasting and Communication, v.15, no.3, pp 32 - 42
- Pages
- 11
- Journal Title
- The International Journal of Internet, Broadcasting and Communication
- Volume
- 15
- Number
- 3
- Start Page
- 32
- End Page
- 42
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/31669
- DOI
- 10.7236/IJIBC.2023.15.3.32
- ISSN
- 2288-4920
2288-4939
- Abstract
- There are serious problems worldwide, such as a pandemic due to an unprecedented infection caused by COVID-19. On previous approaches, they invented medical vaccines and preemptive testing tools for medical engineering. However, it is difficult to access poor medical systems and medical institutions due to disparities between countries and regions. In advanced nations, the damage was even greater due to high medical and examination costs because they did not go to the hospital. Therefore, from a software engineering-based perspective, we propose a learning model for determining coronavirus infection through symptom data-based software prediction models and tools. After a comparative analysis of various models (decision tree, Naive Bayes, KNN, multi-perceptron neural network), we decide to choose an appropriate decision tree model. Due to a lack of data, additional survey data and overseas symptom data are applied and built into the judgment model. To protect from thiswe also adapt human normalization approach with traditional Korean medicin approach. We expect to be possible to determine coronavirus, flu, allergy, and cold without medical examination and diagnosis tools through data collection and analysis by applying decision trees.
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Collections - Graduate School > Software and Communications Engineering > 1. Journal Articles
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