LitCovid-sentences  

PubMed:32982615 JSONTXT 19 Projects

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Id Subject Object Predicate Lexical cue
T1 0-121 Sentence denotes An optimized deep learning architecture for the diagnosis of COVID-19 disease based on gravitational search optimization.
T2 122-296 Sentence denotes In this paper, a novel approach called GSA-DenseNet121-COVID-19 based on a hybrid convolutional neural network (CNN) architecture is proposed using an optimization algorithm.
T3 297-451 Sentence denotes The CNN architecture that was used is called DenseNet121, and the optimization algorithm that was used is called the gravitational search algorithm (GSA).
T4 452-553 Sentence denotes The GSA is used to determine the best values for the hyperparameters of the DenseNet121 architecture.
T5 554-666 Sentence denotes To help this architecture to achieve a high level of accuracy in diagnosing COVID-19 through chest x-ray images.
T6 667-770 Sentence denotes The obtained results showed that the proposed approach could classify 98.38% of the test set correctly.
T7 771-872 Sentence denotes To test the efficacy of the GSA in setting the optimum values for the hyperparameters of DenseNet121.
T8 873-1033 Sentence denotes The GSA was compared to another approach called SSD-DenseNet121, which depends on the DenseNet121 and the optimization algorithm called social ski driver (SSD).
T9 1034-1124 Sentence denotes The comparison results demonstrated the efficacy of the proposed GSA-DenseNet121-COVID-19.
T10 1125-1249 Sentence denotes As it was able to diagnose COVID-19 better than SSD-DenseNet121 as the second was able to diagnose only 94% of the test set.
T11 1250-1408 Sentence denotes The proposed approach was also compared to another method based on a CNN architecture called Inception-v3 and manual search to quantify hyperparameter values.
T12 1409-1581 Sentence denotes The comparison results showed that the GSA-DenseNet121-COVID-19 was able to beat the comparison method, as the second was able to classify only 95% of the test set samples.
T13 1582-1661 Sentence denotes The proposed GSA-DenseNet121-COVID-19 was also compared with some related work.
T14 1662-1742 Sentence denotes The comparison results showed that GSA-DenseNet121-COVID-19 is very competitive.