Your browser doesn't support javascript.
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.
Keywords

Full text: Available 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

Similar

MEDLINE

...
LILACS

LIS


Full text: Available 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