Yu Wang
ABSTRACT
Seasonal pandemics of influenza A viruses bring enormous threaten to human healthy. Different subtypes of influenza A viruses disseminated in human have variable susceptibilities to antiviral drug, so rapid subtyping of influenza A viruses has been increasingly important. Traditional biochemical methods for subtyping these viruses are expensive and time-consuming. Various sequencing techniques and deep learning methods bring an opportunity to analyse and gain information of those biont more conveniently and accurately. This paper proposes a deep convolutional neural network based ensemble learning model to precisely detect all subtypes of influenza A viruses. The experiments show that the proposed method can achieve the state-of-art performance for subtyping influenza A viruses and detecting a fire-new subtypes according to sequence data.
Source Code Available: The source code of this work is accessible on https://github.com/Sophiaaaaaa/Influenza-Subtyping.
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Index Terms
- Rapid Detection and Prediction of Influenza A Subtype using Deep Convolutional Neural Network based Ensemble Learning
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