Journal
JOURNAL OF MEDICAL INTERNET RESEARCH
Volume 22, Issue 12, Pages -Publisher
JMIR PUBLICATIONS, INC
DOI: 10.2196/25442
Keywords
COVID-19; artificial intelligence; blood samples; mortality prediction
Funding
- Korea Medical Device Development Fund - Korean government (the Ministry of Science and ICT)
- Korea Medical Device Development Fund - Korean government (Ministry of Trade, Industry and Energy)
- Korea Medical Device Development Fund - Korean government (Ministry of Health and Welfare, Republic of Korea)
- Korea Medical Device Development Fund - Korean government (Ministry of Food and Drug Safety) [202012B04, NRF-2020R1A2C1014829]
- Korea Health Industry Development Institute [HI18C1216]
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Background: COVID-19, which is accompanied by acute respiratory distress, multiple organ failure, and death, has spread worldwide much faster than previously thought. However, at present, it has limited treatments. Objective: To overcome this issue, we developed an artificial intelligence (AI) model of COVID-19, named EDRnet (ensemble learning model based on deep neural network and random forest models), to predict in-hospital mortality using a routine blood sample at the time of hospital admission. Methods: We selected 28 blood biomarkers and used the age and gender information of patients as model inputs. To improve the mortality prediction, we adopted an ensemble approach combining deep neural network and random forest models. We trained our model with a database of blood samples from 361 COVID-19 patients in Wuhan, China, and applied it to 106 COVID-19 patients in three Korean medical institutions. Results: In the testing data sets, EDRnet provided high sensitivity (100%), specificity (91%), and accuracy (92%). To extend the number of patient data points, we developed a web application (BeatCOVID19) where anyone can access the model to predict mortality and can register his or her own blood laboratory results. Conclusions: Our new AI model, EDRnet, accurately predicts the mortality rate for COVID-19. It is publicly available and aims to help health care providers fight COVID-19 and improve patients' outcomes.
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