{"id":"https://openalex.org/W2810975464","doi":"https://doi.org/10.1109/fskd.2017.8393025","title":"A genetic algorithm based feature selection for binary phenotype prediction using structural brain magnetic resonance imaging","display_name":"A genetic algorithm based feature selection for binary phenotype prediction using structural brain magnetic resonance imaging","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2810975464","doi":"https://doi.org/10.1109/fskd.2017.8393025","mag":"2810975464"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2017.8393025","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2017.8393025","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","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/A5060034830","display_name":"Benteng Ma","orcid":"https://orcid.org/0000-0001-6723-7297"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Benteng Ma","raw_affiliation_strings":["Shaanxi Key Lab of Speech & Image Information Processing (SAIIP), Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Shaanxi Key Lab of Speech & Image Information Processing (SAIIP), Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100670074","display_name":"Yong Xia","orcid":"https://orcid.org/0000-0001-9273-2847"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Xia","raw_affiliation_strings":["Shaanxi Key Lab of Speech & Image Information Processing (SAIIP), Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Shaanxi Key Lab of Speech & Image Information Processing (SAIIP), Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5060034830"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":0.1063,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.50587432,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"6","issue":null,"first_page":"172","last_page":"177"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9937000274658203,"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"}},{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6748110055923462},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6701642274856567},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.664570689201355},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5725407004356384},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.565760612487793},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5166395306587219},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.48083433508872986},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46559441089630127},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.46544349193573},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4624825417995453},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.45935797691345215},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.42637503147125244},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4104246497154236},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4039004445075989},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14496532082557678}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6748110055923462},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6701642274856567},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.664570689201355},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5725407004356384},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.565760612487793},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5166395306587219},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.48083433508872986},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46559441089630127},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.46544349193573},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4624825417995453},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.45935797691345215},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.42637503147125244},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4104246497154236},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4039004445075989},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14496532082557678},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2017.8393025","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2017.8393025","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W140777655","https://openalex.org/W1497256448","https://openalex.org/W1584569974","https://openalex.org/W2002979815","https://openalex.org/W2004338242","https://openalex.org/W2009501510","https://openalex.org/W2014400652","https://openalex.org/W2033511636","https://openalex.org/W2062393208","https://openalex.org/W2072026441","https://openalex.org/W2087678375","https://openalex.org/W2093799708","https://openalex.org/W2098979973","https://openalex.org/W2100253618","https://openalex.org/W2115694019","https://openalex.org/W2116087808","https://openalex.org/W2120216197","https://openalex.org/W2121410881","https://openalex.org/W2133462743","https://openalex.org/W2135190479","https://openalex.org/W2151419026","https://openalex.org/W2154053567","https://openalex.org/W2155925556","https://openalex.org/W2168810081","https://openalex.org/W2256782633","https://openalex.org/W2343420905","https://openalex.org/W2516938563","https://openalex.org/W2735743275","https://openalex.org/W2998216295","https://openalex.org/W4285719527","https://openalex.org/W6629610141","https://openalex.org/W6634810381","https://openalex.org/W6677380243","https://openalex.org/W6683381688","https://openalex.org/W6704978412","https://openalex.org/W6740916260","https://openalex.org/W7066667914"],"related_works":["https://openalex.org/W3204184292","https://openalex.org/W3176564347","https://openalex.org/W1985458517","https://openalex.org/W2355833770","https://openalex.org/W3031039437","https://openalex.org/W3095877357","https://openalex.org/W183202219","https://openalex.org/W2072565696","https://openalex.org/W10861731","https://openalex.org/W2050451745"],"abstract_inverted_index":{"Machine":[0,170],"learning":[1],"methods":[2,158],"have":[3,133,145],"been":[4],"increasingly":[5],"applied":[6],"to":[7,54,78,98,126,132,136,191],"structural":[8,59],"brain":[9,35,60],"magnetic":[10],"resonance":[11],"imaging":[12],"(MRI)":[13],"scans":[14],"for":[15],"predicting":[16],"clinical":[17],"phenotypes":[18],"at":[19],"the":[20,28,31,64,73,81,106,115,120,138,160,167,177,182],"individual":[21],"level.":[22],"Despite":[23],"significant":[24],"methodological":[25],"developments,":[26],"reducing":[27],"dimensionality":[29],"of":[30,66,83,105],"features":[32,85],"extracted":[33],"from":[34],"MRI":[36],"data":[37],"remains":[38],"a":[39,47,90,102],"major":[40],"challenge.":[41],"In":[42],"this":[43],"paper,":[44],"we":[45],"propose":[46],"genetic":[48],"algorithm":[49],"based":[50],"feature":[51,156,184],"selection":[52,157],"approach":[53,149,179],"binary":[55,161,195],"phenotype":[56,162,196],"prediction":[57,163],"using":[58],"MRI.":[61],"We":[62,109,144],"divide":[63],"population":[65],"individuals":[67,125,135],"into":[68,114],"multiple":[69],"tribes":[70],"and":[71,75,153,188],"modify":[72],"initialization":[74],"evolutionary":[76],"operations":[77],"ensure":[79],"that":[80,122,176],"number":[82],"selected":[84],"in":[86,166],"each":[87,94],"tribe":[88,95,112,121],"follows":[89],"Gaussian":[91],"distribution.":[92],"Thus":[93],"is":[96,189],"able":[97,190],"focus":[99],"on":[100,159],"exploring":[101],"specific":[103],"part":[104],"solution":[107,140],"space.":[108],"also":[110],"incorporate":[111],"competition":[113],"evolution":[116],"process,":[117],"which":[118],"allows":[119],"produces":[123],"better":[124],"enlarge":[127],"its":[128],"sizes":[129],"so":[130],"as":[131],"more":[134,186,193],"search":[137],"sub":[139],"space":[141],"it":[142],"explores.":[143],"evaluated":[146],"our":[147],"proposed":[148,178],"against":[150],"eight":[151],"wrapper":[152],"nine":[154],"filter":[155],"dataset":[164],"used":[165],"MICCAI":[168],"2014":[169],"Learning":[171],"Challenge.":[172],"Our":[173],"results":[174],"indicate":[175],"can":[180],"identify":[181],"optimal":[183],"subset":[185],"effectively":[187],"produce":[192],"accurate":[194],"prediction.":[197]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}