A new approach to medical diagnosis
The diagnostic usefulness of artificial neural networks (ANNs) is explored by means of an integrated system for medical diagnosis. The models were developed by using the unsupervized self organizing feature maps algorithm. Clinical and laboratory data for training and testing the ANNs was collected...
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creator | Schizas, C.N. Pattichis, C.S. Middleton, L.T. |
description | The diagnostic usefulness of artificial neural networks (ANNs) is explored by means of an integrated system for medical diagnosis. The models were developed by using the unsupervized self organizing feature maps algorithm. Clinical and laboratory data for training and testing the ANNs was collected from 71 subjects by applying examination protocols that were developed by experts in the appropriate fields. The diagnostic yield obtained by the examined models was in the region of 80 to 90%.< > |
doi_str_mv | 10.1109/IBED.1992.247114 |
format | Conference Proceeding |
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The models were developed by using the unsupervized self organizing feature maps algorithm. Clinical and laboratory data for training and testing the ANNs was collected from 71 subjects by applying examination protocols that were developed by experts in the appropriate fields. 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The models were developed by using the unsupervized self organizing feature maps algorithm. Clinical and laboratory data for training and testing the ANNs was collected from 71 subjects by applying examination protocols that were developed by experts in the appropriate fields. The diagnostic yield obtained by the examined models was in the region of 80 to 90%.< ></description><subject>Artificial neural networks</subject><subject>Diseases</subject><subject>Genetics</subject><subject>Laboratories</subject><subject>Medical diagnosis</subject><subject>Muscles</subject><subject>Neuromuscular</subject><subject>Protocols</subject><subject>Spinal cord</subject><subject>Testing</subject><isbn>9780780307438</isbn><isbn>0780307437</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1992</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj01LAzEURQMiVOrspauA6xnz8jEvWdZatVBw0315ybzRSNsZJgXx31uolwNnd-AK8QCqAVDhafO8fmkgBN1oiwD2RlQBvbpgFFrjZ6Iq5VtdZq0zoO_E41Ke-EfSOE4DpS95HuSRu5zoILtMn6eh5HIvbns6FK7-PRe71_Vu9V5vP942q-W2zj6ca6YUVWvJeJe6iB3qPoWIRjmOmsG30fXICJbAcwqsGDU4Y4Hb6BWzmYvFNZuZeT9O-UjT7_56xPwBnyM83g</recordid><startdate>1992</startdate><enddate>1992</enddate><creator>Schizas, C.N.</creator><creator>Pattichis, C.S.</creator><creator>Middleton, L.T.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1992</creationdate><title>A new approach to medical diagnosis</title><author>Schizas, C.N. ; Pattichis, C.S. ; Middleton, L.T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i89t-eacb064a385cdb7d72fc9b7305eb2e186b5f7e714a18ec9e0e7215341e6b80ee3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1992</creationdate><topic>Artificial neural networks</topic><topic>Diseases</topic><topic>Genetics</topic><topic>Laboratories</topic><topic>Medical diagnosis</topic><topic>Muscles</topic><topic>Neuromuscular</topic><topic>Protocols</topic><topic>Spinal cord</topic><topic>Testing</topic><toplevel>online_resources</toplevel><creatorcontrib>Schizas, C.N.</creatorcontrib><creatorcontrib>Pattichis, C.S.</creatorcontrib><creatorcontrib>Middleton, L.T.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Schizas, C.N.</au><au>Pattichis, C.S.</au><au>Middleton, L.T.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A new approach to medical diagnosis</atitle><btitle>Proceedings of the 1992 International Biomedical Engineering Days</btitle><stitle>IBED</stitle><date>1992</date><risdate>1992</risdate><spage>207</spage><epage>212</epage><pages>207-212</pages><isbn>9780780307438</isbn><isbn>0780307437</isbn><abstract>The diagnostic usefulness of artificial neural networks (ANNs) is explored by means of an integrated system for medical diagnosis. The models were developed by using the unsupervized self organizing feature maps algorithm. Clinical and laboratory data for training and testing the ANNs was collected from 71 subjects by applying examination protocols that were developed by experts in the appropriate fields. The diagnostic yield obtained by the examined models was in the region of 80 to 90%.< ></abstract><pub>IEEE</pub><doi>10.1109/IBED.1992.247114</doi><tpages>6</tpages></addata></record> |
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subjects | Artificial neural networks Diseases Genetics Laboratories Medical diagnosis Muscles Neuromuscular Protocols Spinal cord Testing |
title | A new approach to medical diagnosis |
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