Matches in SemOpenAlex for { <https://semopenalex.org/work/W2969569197> ?p ?o ?g. }
Showing items 1 to 76 of
76
with 100 items per page.
- W2969569197 endingPage "124487" @default.
- W2969569197 startingPage "124487" @default.
- W2969569197 abstract "The detection of abnormal lung sounds collected by electronic stethoscopes plays a fundamental role in pulmonary disease diagnostics for primary care and general patient monitoring in telemedicine. Over the past 40 years, the detection has been performed mainly by supervised learning. This method, however, is time- and cost-consuming, and error-prone because it requires manual labeling large numbers of samples. This work proposes a new method, a graph-based semi-supervised one class support vector machine (OCSVM). It can describe normal lung sounds and detect the abnormal ones only by using a small amount of labeled normal samples and abundant unlabeled samples as training samples, which avoids the shortcomings of the traditional methods. A spectral graph is constructed to indicate the relationship of all the samples, which enriches the information provided by only a small number of labeled normal samples. Then, a graph-based semi-supervised OCSVM model is built and its solution is provided. Employing the information in the spectral graph, the proposed method can enhance the effect of recognition and generalization which are crucial for the effective detection of abnormal lung sounds. Finally, the proposed method is evaluated by experiments with all the samples collected in Shijiazhuang, Hebei province, China. The experimental results show that the method outperforms the original OCSVM when the labeled samples are rare. Meanwhile, the performance of the proposed method becomes better as unlabeled abnormal samples increase." @default.
- W2969569197 created "2019-08-29" @default.
- W2969569197 creator A5007779172 @default.
- W2969569197 creator A5009651652 @default.
- W2969569197 creator A5071092765 @default.
- W2969569197 creator A5073309762 @default.
- W2969569197 creator A5091489017 @default.
- W2969569197 date "2020-01-01" @default.
- W2969569197 modified "2023-10-02" @default.
- W2969569197 title "Graph-based semi-supervised one class support vector machine for detecting abnormal lung sounds" @default.
- W2969569197 cites W1571801203 @default.
- W2969569197 cites W1980128308 @default.
- W2969569197 cites W1989590026 @default.
- W2969569197 cites W2002471315 @default.
- W2969569197 cites W2043392634 @default.
- W2969569197 cites W2075615425 @default.
- W2969569197 cites W2079085607 @default.
- W2969569197 cites W2132870739 @default.
- W2969569197 cites W2132914434 @default.
- W2969569197 cites W2155033583 @default.
- W2969569197 cites W2746612260 @default.
- W2969569197 cites W2794671365 @default.
- W2969569197 cites W2801920224 @default.
- W2969569197 cites W4242314190 @default.
- W2969569197 cites W55501266 @default.
- W2969569197 doi "https://doi.org/10.1016/j.amc.2019.06.001" @default.
- W2969569197 hasPublicationYear "2020" @default.
- W2969569197 type Work @default.
- W2969569197 sameAs 2969569197 @default.
- W2969569197 citedByCount "11" @default.
- W2969569197 countsByYear W29695691972020 @default.
- W2969569197 countsByYear W29695691972021 @default.
- W2969569197 countsByYear W29695691972022 @default.
- W2969569197 countsByYear W29695691972023 @default.
- W2969569197 crossrefType "journal-article" @default.
- W2969569197 hasAuthorship W2969569197A5007779172 @default.
- W2969569197 hasAuthorship W2969569197A5009651652 @default.
- W2969569197 hasAuthorship W2969569197A5071092765 @default.
- W2969569197 hasAuthorship W2969569197A5073309762 @default.
- W2969569197 hasAuthorship W2969569197A5091489017 @default.
- W2969569197 hasConcept C119857082 @default.
- W2969569197 hasConcept C12267149 @default.
- W2969569197 hasConcept C132525143 @default.
- W2969569197 hasConcept C153180895 @default.
- W2969569197 hasConcept C154945302 @default.
- W2969569197 hasConcept C41008148 @default.
- W2969569197 hasConcept C58973888 @default.
- W2969569197 hasConcept C80444323 @default.
- W2969569197 hasConceptScore W2969569197C119857082 @default.
- W2969569197 hasConceptScore W2969569197C12267149 @default.
- W2969569197 hasConceptScore W2969569197C132525143 @default.
- W2969569197 hasConceptScore W2969569197C153180895 @default.
- W2969569197 hasConceptScore W2969569197C154945302 @default.
- W2969569197 hasConceptScore W2969569197C41008148 @default.
- W2969569197 hasConceptScore W2969569197C58973888 @default.
- W2969569197 hasConceptScore W2969569197C80444323 @default.
- W2969569197 hasLocation W29695691971 @default.
- W2969569197 hasOpenAccess W2969569197 @default.
- W2969569197 hasPrimaryLocation W29695691971 @default.
- W2969569197 hasRelatedWork W2041399278 @default.
- W2969569197 hasRelatedWork W2056016498 @default.
- W2969569197 hasRelatedWork W2136184105 @default.
- W2969569197 hasRelatedWork W2160451891 @default.
- W2969569197 hasRelatedWork W2336974148 @default.
- W2969569197 hasRelatedWork W2389470892 @default.
- W2969569197 hasRelatedWork W3013515612 @default.
- W2969569197 hasRelatedWork W3195168932 @default.
- W2969569197 hasRelatedWork W2187500075 @default.
- W2969569197 hasRelatedWork W2345184372 @default.
- W2969569197 hasVolume "364" @default.
- W2969569197 isParatext "false" @default.
- W2969569197 isRetracted "false" @default.
- W2969569197 magId "2969569197" @default.
- W2969569197 workType "article" @default.