한국정보처리학회:학술대회논문집 (Proceedings of the Korea Information Processing Society Conference)
- 한국정보처리학회 2021년도 추계학술발표대회
- /
- Pages.823-826
- /
- 2021
- /
- 2005-0011(pISSN)
- /
- 2671-7298(eISSN)
DOI QR Code
기계학습기반의 코로나 진단 및 증상 분석
Machine Learning based COVID-19 Diagnosis and Symptom Analysis
- 김예담 ;
- Kim, Yedam (Chadwick International School) ;
- Trivino, Stuart (Chadwick International School)
- 발행 : 2021.11.04
초록
The recent COVID-19 pandemic has accentuated the need for faster and more accurate ways of diagnosing certain diseases for there to be safer and more effective early responses that help to prevent a total outbreak. In this work, we would like to approach this issue through machine learning algorithms to investigate whether or not they could serve as a viable replacement for conventional diagnosis. Through a process of training and testing various algorithms, we analyzed how successfully they can predict a patient's COVID-19 diagnosis based on a list of symptoms and also identified which algorithm is the most effective at doing so. If the necessary data, containing the symptoms and diagnoses of different cases, is provided, this method can be utilized to make a probable diagnosis of any disease besides COVID-19. This method can be used in conjunction with or in lieu of conventional diagnosis depending on the situation: if there is a lack of testing facilities or test kits, this method can be employed as it is inexhaustible and it could also be used in situations where a conventional diagnosis is proven to be inaccurate.
키워드