Journal of Antivirals & Antiretrovirals

Journal of Antivirals & Antiretrovirals
Open Access

ISSN: 1948-5964

Yining Dai

Department of Infectious Diseases, Zhejiang Provisional People’s Hospital, People’s Hospital of Hangzhou Medical College, Hangzhou, China

  • Research Article   
    A Prediction Model Based on Machine Learning for Diagnosing the Early COVID-19 Patients
    Author(s): Nannan Sun, Ya Yang, Lingling Tang, Zhen Li, Yining Dai, Wan Xu, Xiaoliang Qian, Hainv Gao and Bin Ju*

    Objective: To improve the timeliness for the early COVID-19 infection diagnosis, it is essential to develop a decision- making tool to assist early diagnosis of COVID-19 patients in fever clinics. Materials and methods: This paper aims at extracting risk factors from clinical data of 912 early COVID-19 infected patients and utilizing four types of traditional machine learning approaches including Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF) and a deep learning-based method for diagnosis of early COVID-19. Results: The results show that the LR predictive model presents a higher specificity rate of 0.95, an Area Under the receiver operating Curve (AUC) of 0.971 and an improved sensitivity rate of 0.82, which makes it optimal for the screening of early COVID-19 infection. .. View More»
    DOI: 10.35248/1948-5964.21.s18.002

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