Matches in SemOpenAlex for { <https://semopenalex.org/work/W4214905507> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W4214905507 abstract "COVID-19 is one of the major health crises worldwide. Though number of vaccines is introduced by many countries but still it is challenging to detect the disease at early stage. Many advanced technologies are introduced for this purpose to stop the spread. Machine learning based COVID detection can be a supportive tool for both physicians as well as patients for early prediction of this illness. Different automated technologies are also found from the literature for this purpose. Deep learning approach is used for predicting the infection probability by analyzing the five types of COVID symptoms. The experiment is carried out with 2889 samples collected from a publicly available database. A deep neural network (DNN) classifier is designed for this purpose and the result is also compared with support vector machine (SVM). From the result it is observed that around 97% classification accuracy is observed with DNN classifier and it is better than SVM." @default.
- W4214905507 created "2022-03-05" @default.
- W4214905507 creator A5066771115 @default.
- W4214905507 creator A5068303862 @default.
- W4214905507 creator A5078109475 @default.
- W4214905507 creator A5087168579 @default.
- W4214905507 date "2021-12-01" @default.
- W4214905507 modified "2023-09-27" @default.
- W4214905507 title "A Deep Learning Approach for COVID-19 Infection Probability Prediction" @default.
- W4214905507 cites W2891920841 @default.
- W4214905507 cites W3012994592 @default.
- W4214905507 cites W3016697875 @default.
- W4214905507 cites W3017117984 @default.
- W4214905507 cites W3019186020 @default.
- W4214905507 cites W3020229006 @default.
- W4214905507 cites W3025352604 @default.
- W4214905507 cites W3085954833 @default.
- W4214905507 cites W3096215591 @default.
- W4214905507 cites W3203206344 @default.
- W4214905507 cites W4239510810 @default.
- W4214905507 doi "https://doi.org/10.1109/ocit53463.2021.00057" @default.
- W4214905507 hasPublicationYear "2021" @default.
- W4214905507 type Work @default.
- W4214905507 citedByCount "1" @default.
- W4214905507 countsByYear W42149055072022 @default.
- W4214905507 crossrefType "proceedings-article" @default.
- W4214905507 hasAuthorship W4214905507A5066771115 @default.
- W4214905507 hasAuthorship W4214905507A5068303862 @default.
- W4214905507 hasAuthorship W4214905507A5078109475 @default.
- W4214905507 hasAuthorship W4214905507A5087168579 @default.
- W4214905507 hasConcept C108583219 @default.
- W4214905507 hasConcept C116675565 @default.
- W4214905507 hasConcept C119857082 @default.
- W4214905507 hasConcept C12267149 @default.
- W4214905507 hasConcept C142724271 @default.
- W4214905507 hasConcept C154945302 @default.
- W4214905507 hasConcept C159047783 @default.
- W4214905507 hasConcept C2779134260 @default.
- W4214905507 hasConcept C3006700255 @default.
- W4214905507 hasConcept C3007834351 @default.
- W4214905507 hasConcept C3008058167 @default.
- W4214905507 hasConcept C41008148 @default.
- W4214905507 hasConcept C50644808 @default.
- W4214905507 hasConcept C524204448 @default.
- W4214905507 hasConcept C71924100 @default.
- W4214905507 hasConcept C95623464 @default.
- W4214905507 hasConceptScore W4214905507C108583219 @default.
- W4214905507 hasConceptScore W4214905507C116675565 @default.
- W4214905507 hasConceptScore W4214905507C119857082 @default.
- W4214905507 hasConceptScore W4214905507C12267149 @default.
- W4214905507 hasConceptScore W4214905507C142724271 @default.
- W4214905507 hasConceptScore W4214905507C154945302 @default.
- W4214905507 hasConceptScore W4214905507C159047783 @default.
- W4214905507 hasConceptScore W4214905507C2779134260 @default.
- W4214905507 hasConceptScore W4214905507C3006700255 @default.
- W4214905507 hasConceptScore W4214905507C3007834351 @default.
- W4214905507 hasConceptScore W4214905507C3008058167 @default.
- W4214905507 hasConceptScore W4214905507C41008148 @default.
- W4214905507 hasConceptScore W4214905507C50644808 @default.
- W4214905507 hasConceptScore W4214905507C524204448 @default.
- W4214905507 hasConceptScore W4214905507C71924100 @default.
- W4214905507 hasConceptScore W4214905507C95623464 @default.
- W4214905507 hasLocation W42149055071 @default.
- W4214905507 hasOpenAccess W4214905507 @default.
- W4214905507 hasPrimaryLocation W42149055071 @default.
- W4214905507 hasRelatedWork W2803710604 @default.
- W4214905507 hasRelatedWork W3036314732 @default.
- W4214905507 hasRelatedWork W3136979370 @default.
- W4214905507 hasRelatedWork W3158264953 @default.
- W4214905507 hasRelatedWork W4205317059 @default.
- W4214905507 hasRelatedWork W4206669628 @default.
- W4214905507 hasRelatedWork W4285106639 @default.
- W4214905507 hasRelatedWork W4308496516 @default.
- W4214905507 hasRelatedWork W4310989423 @default.
- W4214905507 hasRelatedWork W4311106074 @default.
- W4214905507 isParatext "false" @default.
- W4214905507 isRetracted "false" @default.
- W4214905507 workType "article" @default.