作者
Joseph Bamidele Awotunde, Sunday Adeola Ajagbe, Matthew A Oladipupo, Jimmisayo A Awokola, Olakunle S Afolabi, Timothy O Mathew, Yetunde J Oguns
发表日期
2021/10/23
图书
International Conference on Applied Informatics
页码范围
319-330
出版商
Springer International Publishing
简介
The pandemic produced by coronavirus2 (COVID-19) has confined the world, and avoiding close human contact is still suggested to combat the outbreak although the vaccination campaigns. It is expectable that emerging technologies have prominent roles to play during this pandemic, and the use of Artificial Intelligence (AI) has been proved useful in this direction. The use of AI by researchers in developing novel models for diagnosis, classification, and prediction of COVID-19 has really assist reduce the spread of the outbreak. Therefore, this paper proposes a machine learning diagnostic system to combat the spread of COVID-19. Four machine learning algorithms: Random Forest (RF), XGBoost, and Light Gradient Boosting Machine (LGBM) were used for quick and better identification of potential COVID-19 cases. The dataset used contains COVID-19 symptoms and selects the relevant symptoms of the …
引用总数
学术搜索中的文章
JB Awotunde, SA Ajagbe, MA Oladipupo, JA Awokola… - International Conference on Applied Informatics, 2021