DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hyeon, Jonghwan | ko |
dc.contributor.author | Choi, Ho-Jin | ko |
dc.contributor.author | Lee, Byung Doo | ko |
dc.contributor.author | Lee, Kap No | ko |
dc.date.accessioned | 2018-01-23T01:16:22Z | - |
dc.date.available | 2018-01-23T01:16:22Z | - |
dc.date.created | 2017-12-28 | - |
dc.date.created | 2017-12-28 | - |
dc.date.issued | 2017-02-13 | - |
dc.identifier.citation | 2nd Int’l Workshop on Big Data Analytics for Healthcare and Well-being (BigData4Healthcare 2017), Workshop on 2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017, pp.390 - 393 | - |
dc.identifier.uri | http://hdl.handle.net/10203/237792 | - |
dc.description.abstract | Cervical cancer is a disease that affects 266,000 deaths worldwide and is the fourth highest incidence of cancer in women. This cancer can be diagnosed through a Pap smear, where a cytopathologist observes a microscopic image of the cervix cells to determine whether the patient is normal or abnormal. The sensitivity and specificity of the Pap smear is known to be respectively 53.4% and 69.2%. Since the test is related to the patient's life, it is important to improve the accuracy of the test. A variety of systems have been proposed to help judge experts to improve the accuracy of tests in the medical field, but the development of these systems has been limited to areas where digitized test data are clearly present. In this paper, we design and propose a model that automatically classifies normal/abnormal states of cervical cells from microscopic images using convolutional neural network and several machine learning classifiers. As a result, the support vector machine showed the best performance with a 78% F1 score. | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Diagnosing Cervical Cell Images Using Pre-trained Convolutional Neural Network as Feature Extractor | - |
dc.type | Conference | - |
dc.identifier.wosid | 000403390900065 | - |
dc.identifier.scopusid | 2-s2.0-85017611781 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 390 | - |
dc.citation.endingpage | 393 | - |
dc.citation.publicationname | 2nd Int’l Workshop on Big Data Analytics for Healthcare and Well-being (BigData4Healthcare 2017), Workshop on 2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017 | - |
dc.identifier.conferencecountry | KO | - |
dc.identifier.conferencelocation | Maison Glad Jeju | - |
dc.identifier.doi | 10.1109/BIGCOMP.2017.7881741 | - |
dc.contributor.localauthor | Choi, Ho-Jin | - |
dc.contributor.nonIdAuthor | Lee, Byung Doo | - |
dc.contributor.nonIdAuthor | Lee, Kap No | - |
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