Pervasive Intelligent Models to Predict the Outcome of COVID-19 Patients
نویسندگان
چکیده
Nowadays, there is an increasing need to understand the behavior of COVID-19. After Directorate-General Health Portugal made available infected patient’s data, it became possible analyze and gather some conclusions, obtaining a better understanding matter. In this context, project developed—ioCOVID19—Intelligent Decision Support Platform aims identify patterns develop intelligent models predict support clinical decisions. This article explores which typologies are associated with different outcomes help clinicians fight virus decision system. So, achieve purpose, classification algorithms were used, one target was studied—Patients outcome, that is, if patient will die or recover. Regarding obtained results, model stood out composed scenario s4 (composed all comorbidities, symptoms, age), tree algorithm, oversampling sampling method. The results by studied metrics (in order importance): Sensitivity 95.20%, Accuracy 90.67%, Specificity 86.08%. deployed as service, they part system for authorized users anywhere anytime.
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ژورنال
عنوان ژورنال: Future Internet
سال: 2021
ISSN: ['1999-5903']
DOI: https://doi.org/10.3390/fi13040102