Design and analysis on molecular level biomedical event trigger extraction using recurrent neural network-based particle swarm optimisation for COVID-19 research
by R.N. Devendra Kumar; Arvind Chakrapani; Srihari Kannan
International Journal of Computer Applications in Technology (IJCAT), Vol. 66, No. 3/4, 2021

Abstract: In this paper, the rich extracted feature sets are fed to the deep learning classifier that estimates the optimal extraction of lung molecule triggered events for COVID-19 infections. The feature extraction is carried out using Recurrent Neural Network (RNN) that effectively extracts the features from the rich data sets. Secondly, a Particle Swarm Optimisation (PSO) algorithm is utilised to classify the extracted features of COVID-19 infections. The rule set for feature extractor is supplied by the fuzzy logic rule set. The simulation shows that the RNN-PSO, which is the combination of two different algorithms, offers better performance than other machine learning classifiers.

Online publication date: Fri, 21-Jan-2022

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