Rapid Detection and Prediction of Influenza A Subtype using Deep Convolutional Neural Network based Ensemble Learning
| Autor: | Yongfeng Li, Yu Wang, Jianqiang Du, JunPeng Bao |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Source code Computer science medicine.drug_class business.industry media_common.quotation_subject Deep learning 0206 medical engineering Influenza a 02 engineering and technology Computational biology Ensemble learning Convolutional neural network Subtyping 03 medical and health sciences 030104 developmental biology Pandemic medicine Artificial intelligence Antiviral drug business 020602 bioinformatics media_common |
| Zdroj: | Proceedings of the 2020 10th International Conference on Bioscience, Biochemistry and Bioinformatics. |
| DOI: | 10.1145/3386052.3386053 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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