Matches in SemOpenAlex for { <https://semopenalex.org/work/W4312771890> ?p ?o ?g. }
Showing items 1 to 70 of
70
with 100 items per page.
- W4312771890 endingPage "631" @default.
- W4312771890 startingPage "625" @default.
- W4312771890 abstract "This paper highlights the role of evolving spiking neural networks (an enhanced version of SNN) for predicting medical diagnosis. This article aims to focus on regression problems under a supervised learning strategy. In this paper, we have trained and tested eSNN on benchmarking datasets. Among the three datasets, one is the ICU Dataset which helps in predicting the recovery ration of patients who stayed in ICU. Another dataset is Plasma_Retinol which predicts the risk of cancer-related to certain carotenoids. Dataset pharynx is a part of a study conducted in the USA to determine the success rate of two radiation types. The selected datasets are those which were previously used for BioMedical Engineering related tasks. Later the evaluation was conducted using Regression Metrics. From experiment results, it is concluded that eSNN with standard parameters without optimization performed well but there is still space available for improvement to achieve the highest possible prediction scores." @default.
- W4312771890 created "2023-01-05" @default.
- W4312771890 creator A5026473778 @default.
- W4312771890 creator A5028915945 @default.
- W4312771890 creator A5030204424 @default.
- W4312771890 date "2022-01-01" @default.
- W4312771890 modified "2023-10-17" @default.
- W4312771890 title "Evolving Spiking Neural Network for Prediction Problems in Healthcare System" @default.
- W4312771890 cites W1063476113 @default.
- W4312771890 cites W1496832825 @default.
- W4312771890 cites W2068566049 @default.
- W4312771890 cites W2086849006 @default.
- W4312771890 cites W2122987204 @default.
- W4312771890 cites W2125791732 @default.
- W4312771890 cites W2171043895 @default.
- W4312771890 cites W2184268905 @default.
- W4312771890 cites W2398571562 @default.
- W4312771890 cites W2619470770 @default.
- W4312771890 cites W2792257992 @default.
- W4312771890 cites W2885060605 @default.
- W4312771890 cites W47480302 @default.
- W4312771890 cites W70449568 @default.
- W4312771890 doi "https://doi.org/10.1007/978-981-16-2183-3_60" @default.
- W4312771890 hasPublicationYear "2022" @default.
- W4312771890 type Work @default.
- W4312771890 citedByCount "0" @default.
- W4312771890 crossrefType "book-chapter" @default.
- W4312771890 hasAuthorship W4312771890A5026473778 @default.
- W4312771890 hasAuthorship W4312771890A5028915945 @default.
- W4312771890 hasAuthorship W4312771890A5030204424 @default.
- W4312771890 hasConcept C105795698 @default.
- W4312771890 hasConcept C119857082 @default.
- W4312771890 hasConcept C144133560 @default.
- W4312771890 hasConcept C152877465 @default.
- W4312771890 hasConcept C154945302 @default.
- W4312771890 hasConcept C162853370 @default.
- W4312771890 hasConcept C33923547 @default.
- W4312771890 hasConcept C41008148 @default.
- W4312771890 hasConcept C50644808 @default.
- W4312771890 hasConcept C83546350 @default.
- W4312771890 hasConcept C86251818 @default.
- W4312771890 hasConceptScore W4312771890C105795698 @default.
- W4312771890 hasConceptScore W4312771890C119857082 @default.
- W4312771890 hasConceptScore W4312771890C144133560 @default.
- W4312771890 hasConceptScore W4312771890C152877465 @default.
- W4312771890 hasConceptScore W4312771890C154945302 @default.
- W4312771890 hasConceptScore W4312771890C162853370 @default.
- W4312771890 hasConceptScore W4312771890C33923547 @default.
- W4312771890 hasConceptScore W4312771890C41008148 @default.
- W4312771890 hasConceptScore W4312771890C50644808 @default.
- W4312771890 hasConceptScore W4312771890C83546350 @default.
- W4312771890 hasConceptScore W4312771890C86251818 @default.
- W4312771890 hasLocation W43127718901 @default.
- W4312771890 hasOpenAccess W4312771890 @default.
- W4312771890 hasPrimaryLocation W43127718901 @default.
- W4312771890 hasRelatedWork W1970158984 @default.
- W4312771890 hasRelatedWork W2010246604 @default.
- W4312771890 hasRelatedWork W2012241321 @default.
- W4312771890 hasRelatedWork W2045877109 @default.
- W4312771890 hasRelatedWork W2072034916 @default.
- W4312771890 hasRelatedWork W2183168381 @default.
- W4312771890 hasRelatedWork W2359645249 @default.
- W4312771890 hasRelatedWork W3098038161 @default.
- W4312771890 hasRelatedWork W4289765664 @default.
- W4312771890 hasRelatedWork W1629725936 @default.
- W4312771890 isParatext "false" @default.
- W4312771890 isRetracted "false" @default.
- W4312771890 workType "book-chapter" @default.