Clinical Characteristics of COVID-19 Patients and Application to an Artificial Intelligence System for Disease Surveillance.

Ying-Chuan Wang,Kuo-Ming Yeh,Feng-Yee Chang,Chun-Hsiang Chiu,Li-Chen Yen,Dung-Jang Tsai,Ya-Hsin Yao,Te-Yu Lin,Tsung-Ta Chiang

doi:10.3390/jcm11051437

Abstract

During the coronavirus disease (COVID-19) pandemic, we admitted suspected or confirmed COVID-19 patients to our isolation wards between 2 March 2020 and 4 May 2020, following a well-designed and efficient assessment protocol. We included 217 patients suspected of COVID-19, of which 27 had confirmed COVID-19. The clinical characteristics of these patients were used to train artificial intelligence (AI) models such as support vector machine (SVM), decision tree, random forest, and artificial neural network for diagnosing COVID-19. When analyzing the performance of the models, SVM showed the highest sensitivity (SVM vs. decision tree vs. random forest vs. artificial neural network: 100% vs. 42.86% vs. 28.57% vs. 71.43%), while decision tree and random forest had the highest specificity (SVM vs. decision tree vs. random forest vs. artificial neural network: 88.37% vs. 100% vs. 100% vs. 94.74%) in the diagnosis of COVID-19. With the aid of AI models, physicians may identify COVID-19 patients earlier, even with few baseline data available, and segregate infected patients earlier to avoid hospital cluster infections and to ensure the safety of medical professionals and ordinary patients in the hospital.

Highlights

Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
From 2 March 2020 to 4 May 2020, there were 217 cases suspected of COVID-19 who were admitted to our isolation ward at Tri Service General Hospital
We describe a model to early detect COVID-19 infection by inputting clinical characteristics and routine lab data which is more feasible and economic than routine expensive examinations such as chest computed tomography (CT)

Summary

Introduction

Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The clinical spectrum of COVID-19 appears to be broad, ranging from no symptoms to mild upper respiratory tract illness, severe pneumonia with respiratory failure, and death. The early diagnosis of asymptomatic or mild COVID-19 patients is essential to prevent the spread of the infection during the pandemic. Researchers found that well-trained artificial intelligence (AI) can ensure accurate and rapid diagnosis or assist physicians to reduce manual labor. Some of these studies were conducted for AI-assisted COVID-19 diagnosis [1–18], some were conducted for predicting the prognosis of patients [19–28], and others were conducted for predicting the epidemic trend of COVID-19 [29–31]

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