Modeling Influenza with a Forest Deep Neural Network Utilizing a Virtualized Clinical Semantic Network
2021 IEEE International Conference on Big Data, Big Data 2021
; : 4753-4760, 2021.
Article
in English
| Scopus | ID: covidwho-1730864
ABSTRACT
CoViD-19 pandemic has shown that we have deep gaps in understanding this extremely infectious virus - not only both from a clinical diagnosis and treatment perspective - but also from a forecasting point of view, so that we are better prepared for the next onset of a similar pandemic, which, at this point, seems almost inevitable. In this paper, we present a novel approach towards modeling influenza, a closely related disease to CoViD-19, marrying clinical understanding with artificial intelligence, exploiting the Forest Deep Neural Network (fDNN) with accuracy rates in the 90% range. © 2021 IEEE.
Full text:
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Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
Language:
English
Journal:
2021 IEEE International Conference on Big Data, Big Data 2021
Year:
2021
Document Type:
Article
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