{"id":"https://openalex.org/W2073486526","doi":"https://doi.org/10.1109/scis-isis.2012.6505295","title":"Hybrid feedback GMDH-type neural network self-selecting various neurons and its application to medical image diagnosis of lung cancer","display_name":"Hybrid feedback GMDH-type neural network self-selecting various neurons and its application to medical image diagnosis of lung cancer","publication_year":2012,"publication_date":"2012-11-01","ids":{"openalex":"https://openalex.org/W2073486526","doi":"https://doi.org/10.1109/scis-isis.2012.6505295","mag":"2073486526"},"language":"en","primary_location":{"id":"doi:10.1109/scis-isis.2012.6505295","is_oa":false,"landing_page_url":"https://doi.org/10.1109/scis-isis.2012.6505295","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058822913","display_name":"Tadashi Kondo","orcid":"https://orcid.org/0000-0001-6405-7792"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]},{"id":"https://openalex.org/I922474255","display_name":"Tokushima University","ror":"https://ror.org/044vy1d05","country_code":"JP","type":"education","lineage":["https://openalex.org/I922474255"]}],"countries":["AU","JP"],"is_corresponding":false,"raw_author_name":"Tadashi Kondo","raw_affiliation_strings":["Graduate School of Health Sciences, University of Tokushima, Tokushima, Japan","Graduate School of Health Sciences, The University of Tokushima, 3-18-15 Kuramoto-cho Tokushima, 770-8509 Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Health Sciences, University of Tokushima, Tokushima, Japan","institution_ids":["https://openalex.org/I922474255"]},{"raw_affiliation_string":"Graduate School of Health Sciences, The University of Tokushima, 3-18-15 Kuramoto-cho Tokushima, 770-8509 Japan","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025328715","display_name":"Junji Ueno","orcid":null},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]},{"id":"https://openalex.org/I922474255","display_name":"Tokushima University","ror":"https://ror.org/044vy1d05","country_code":"JP","type":"education","lineage":["https://openalex.org/I922474255"]}],"countries":["AU","JP"],"is_corresponding":false,"raw_author_name":"Junji Ueno","raw_affiliation_strings":["Graduate School of Health Sciences, University of Tokushima, Tokushima, Japan","Graduate School of Health Sciences, The University of Tokushima, 3-18-15 Kuramoto-cho Tokushima, 770-8509 Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Health Sciences, University of Tokushima, Tokushima, Japan","institution_ids":["https://openalex.org/I922474255"]},{"raw_affiliation_string":"Graduate School of Health Sciences, The University of Tokushima, 3-18-15 Kuramoto-cho Tokushima, 770-8509 Japan","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063644448","display_name":"Schoichiro Takao","orcid":null},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]},{"id":"https://openalex.org/I922474255","display_name":"Tokushima University","ror":"https://ror.org/044vy1d05","country_code":"JP","type":"education","lineage":["https://openalex.org/I922474255"]}],"countries":["AU","JP"],"is_corresponding":false,"raw_author_name":"Schoichiro Takao","raw_affiliation_strings":["Graduate School of Health Sciences, University of Tokushima, Tokushima, Japan","Graduate School of Health Sciences, The University of Tokushima, 3-18-15 Kuramoto-cho Tokushima, 770-8509 Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Health Sciences, University of Tokushima, Tokushima, Japan","institution_ids":["https://openalex.org/I922474255"]},{"raw_affiliation_string":"Graduate School of Health Sciences, The University of Tokushima, 3-18-15 Kuramoto-cho Tokushima, 770-8509 Japan","institution_ids":["https://openalex.org/I82951845"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4423,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.7325503,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"5","issue":null,"first_page":"1925","last_page":"1930"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14351","display_name":"Statistical and Computational Modeling","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14351","display_name":"Statistical and Computational Modeling","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7399764060974121},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6714760065078735},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5425920486450195},{"id":"https://openalex.org/keywords/group-method-of-data-handling","display_name":"Group method of data handling","score":0.48195788264274597},{"id":"https://openalex.org/keywords/cad","display_name":"CAD","score":0.4796367287635803},{"id":"https://openalex.org/keywords/feedforward-neural-network","display_name":"Feedforward neural network","score":0.4557613134384155},{"id":"https://openalex.org/keywords/sigmoid-function","display_name":"Sigmoid function","score":0.44423818588256836},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42004287242889404},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.41766947507858276},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23834896087646484},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10498028993606567}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7399764060974121},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6714760065078735},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5425920486450195},{"id":"https://openalex.org/C13926793","wikidata":"https://www.wikidata.org/wiki/Q3507155","display_name":"Group method of data handling","level":2,"score":0.48195788264274597},{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.4796367287635803},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.4557613134384155},{"id":"https://openalex.org/C81388566","wikidata":"https://www.wikidata.org/wiki/Q526668","display_name":"Sigmoid function","level":3,"score":0.44423818588256836},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42004287242889404},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.41766947507858276},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23834896087646484},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10498028993606567},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/scis-isis.2012.6505295","is_oa":false,"landing_page_url":"https://doi.org/10.1109/scis-isis.2012.6505295","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8100000023841858,"display_name":"Good health and well-being"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W351653889","https://openalex.org/W566563139","https://openalex.org/W928885820","https://openalex.org/W1770912791","https://openalex.org/W1998481530","https://openalex.org/W2055823751","https://openalex.org/W2142075297","https://openalex.org/W2142635246","https://openalex.org/W4300945981","https://openalex.org/W6611813326","https://openalex.org/W6615861991"],"related_works":["https://openalex.org/W1521636419","https://openalex.org/W2086501033","https://openalex.org/W2041493034","https://openalex.org/W271423343","https://openalex.org/W2393674365","https://openalex.org/W3116482746","https://openalex.org/W2150273373","https://openalex.org/W1595652908","https://openalex.org/W2089093251","https://openalex.org/W2762260865"],"abstract_inverted_index":{"Hybrid":[0],"feedback":[1,87,98],"Group":[2],"Method":[3],"of":[4,22,30,55,70,97,102,131,137,159,173],"Data":[5],"Handling":[6],"(GMDH)-type":[7],"neural":[8,31,37,43,47,60,78,84,125,139,167],"network":[9,44,61,79,85,126,168],"self-selecting":[10],"various":[11],"neurons":[12,103],"is":[13,64,73,127,162,169],"applied":[14,128],"to":[15,117,129],"the":[16,59,65,68,90,95,100,108,119,153],"computer":[17],"aided":[18],"image":[19],"diagnosis":[20],"(CAD)":[21],"lung":[23,132,143,146,174],"cancer.":[24,175],"In":[25],"this":[26,82,165],"algorithm,":[27],"three":[28,53,77],"types":[29,54],"networks,":[32],"such":[33,93],"as":[34,94,116],"sigmoid":[35],"function":[36,41],"network,":[38,48],"radial":[39],"basis":[40],"(RBF)":[42],"and":[45,58,89,107,134,145],"polynomial":[46],"can":[49],"be":[50],"generated":[51,151],"using":[52],"neuron":[56],"architectures,":[57],"architecture":[62],"which":[63,141],"most":[66],"fit":[67],"complexity":[69],"medical":[71],"images,":[72],"selected":[74,114],"from":[75,152],"these":[76],"architectures.":[80],"Furthermore,":[81],"GMDH-type":[83,124,138,166],"has":[86],"loop":[88],"structural":[91],"parameters":[92],"number":[96,101],"loops,":[99],"in":[104],"hidden":[105],"layers":[106],"relevant":[109],"input":[110],"variables":[111],"are":[112,149],"automatically":[113,150],"so":[115],"minimize":[118],"prediction":[120],"error":[121],"criterion.":[122],"This":[123],"CAD":[130,172],"cancer":[133,147],"two":[135],"kinds":[136],"networks":[140],"recognize":[142],"regions":[144],"regions,":[148],"multi-detector":[154],"row":[155],"CT":[156],"(MDCT)":[157],"images":[158],"lungs.":[160],"It":[161],"shown":[163],"that":[164],"useful":[170],"for":[171]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}