{"id":"https://openalex.org/W4411600598","doi":"https://doi.org/10.1109/cec65147.2025.11043090","title":"Multitree GP-Based Feature Learning for Multimodal Medical Image Classification","display_name":"Multitree GP-Based Feature Learning for Multimodal Medical Image Classification","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4411600598","doi":"https://doi.org/10.1109/cec65147.2025.11043090"},"language":"en","primary_location":{"id":"doi:10.1109/cec65147.2025.11043090","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec65147.2025.11043090","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Congress on Evolutionary Computation (CEC)","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/A5032994747","display_name":"Zhicheng Wu","orcid":"https://orcid.org/0000-0003-3498-7520"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Zhicheng Wu","raw_affiliation_strings":["Victoria University of Wellington,Centre for Data Science and Artificial Intelligence & School of Engineering and Computer Science,Wellington,New Zealand,6140"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington,Centre for Data Science and Artificial Intelligence & School of Engineering and Computer Science,Wellington,New Zealand,6140","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077569089","display_name":"Bing Xue","orcid":"https://orcid.org/0000-0002-4865-8026"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Bing Xue","raw_affiliation_strings":["Victoria University of Wellington,Centre for Data Science and Artificial Intelligence & School of Engineering and Computer Science,Wellington,New Zealand,6140"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington,Centre for Data Science and Artificial Intelligence & School of Engineering and Computer Science,Wellington,New Zealand,6140","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100400258","display_name":"Mengjie Zhang","orcid":"https://orcid.org/0000-0003-4463-9538"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Mengjie Zhang","raw_affiliation_strings":["Victoria University of Wellington,Centre for Data Science and Artificial Intelligence & School of Engineering and Computer Science,Wellington,New Zealand,6140"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington,Centre for Data Science and Artificial Intelligence & School of Engineering and Computer Science,Wellington,New Zealand,6140","institution_ids":["https://openalex.org/I41156924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10865938,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.8213000297546387,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.8213000297546387,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10862","display_name":"AI in cancer detection","score":0.7558000087738037,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.7028999924659729,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7281008362770081},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6397870182991028},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6147125363349915},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5313870310783386},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.505659818649292},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46610531210899353},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4377603530883789},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39570051431655884}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7281008362770081},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6397870182991028},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6147125363349915},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5313870310783386},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.505659818649292},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46610531210899353},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4377603530883789},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39570051431655884},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec65147.2025.11043090","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec65147.2025.11043090","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W148115400","https://openalex.org/W2027649639","https://openalex.org/W2044465660","https://openalex.org/W2079217673","https://openalex.org/W2161969291","https://openalex.org/W2163808566","https://openalex.org/W2165097780","https://openalex.org/W2343420905","https://openalex.org/W2485116416","https://openalex.org/W2732300860","https://openalex.org/W2907760128","https://openalex.org/W2968787142","https://openalex.org/W2969199043","https://openalex.org/W2973731007","https://openalex.org/W2996092187","https://openalex.org/W3036020790","https://openalex.org/W3128869102","https://openalex.org/W3133356497","https://openalex.org/W3199439616","https://openalex.org/W3215150387","https://openalex.org/W4226216634","https://openalex.org/W4229332619","https://openalex.org/W4237313096","https://openalex.org/W4318344284","https://openalex.org/W4379652941","https://openalex.org/W4380628094","https://openalex.org/W4386826466","https://openalex.org/W4388052835","https://openalex.org/W4393372413","https://openalex.org/W4398202743","https://openalex.org/W4399939469","https://openalex.org/W4400526215","https://openalex.org/W4401513025","https://openalex.org/W4403211653","https://openalex.org/W6703031276","https://openalex.org/W6713455525"],"related_works":["https://openalex.org/W2601157893","https://openalex.org/W2373006798","https://openalex.org/W2131735617","https://openalex.org/W2056912418","https://openalex.org/W2033213769","https://openalex.org/W4312376745","https://openalex.org/W2136016640","https://openalex.org/W2049538278","https://openalex.org/W2886173746","https://openalex.org/W4200043248"],"abstract_inverted_index":{"Multimodal":[0,107],"medical":[1,19,54,91,162],"image":[2,55],"classification":[3,156],"(MMIC)":[4],"refers":[5],"to":[6,17,41,111],"the":[7,59,144,178,195,201],"process":[8,61],"of":[9,143,204],"extracting":[10],"and":[11,87,126,134,157,171,186],"combining":[12],"information":[13],"from":[14,31,47,117],"various":[15],"modalities":[16,33],"classify":[18],"images,":[20],"ultimately":[21],"improving":[22],"diagnostic":[23],"accuracy.":[24],"Most":[25],"existing":[26],"methods":[27,82],"extract":[28,113],"discriminative":[29],"features":[30,125],"different":[32,118,161,205],"for":[34,74],"specific":[35],"tasks":[36],"but":[37],"often":[38],"lack":[39],"adaptability":[40],"other":[42],"tasks.":[43],"Additionally,":[44],"they":[45],"suffer":[46],"poor":[48],"interpretability,":[49],"which":[50],"is":[51,62,147],"critical":[52],"in":[53,90],"analysis,":[56],"as":[57],"understanding":[58],"decision-making":[60],"essential.":[63],"Genetic":[64],"programming":[65],"(GP),":[66],"particularly":[67],"multitree":[68,80,104],"GP,":[69],"provides":[70],"a":[71,102],"flexible":[72],"framework":[73],"evolving":[75],"multimodal":[76,92,128,172,188],"features.":[77],"However,":[78],"current":[79],"GP":[81,105,109],"only":[83],"perform":[84],"feature-level":[85,132],"fusion":[86,133,136],"remain":[88],"underexplored":[89],"feature":[93,115],"learning.":[94],"To":[95,120],"address":[96],"these":[97],"issues,":[98],"this":[99],"paper":[100],"proposes":[101],"novel":[103],"method,":[106],"Feature":[108],"(MFGP),":[110],"automatically":[112],"informative":[114],"vectors":[116],"modalities.":[119,206],"fully":[121],"utilize":[122],"both":[123,169],"modality-specific":[124],"fused":[127],"features,":[129],"we":[130],"integrate":[131],"decision-level":[135],"strategies":[137],"into":[138],"our":[139],"framework.":[140],"The":[141,164],"performance":[142],"proposed":[145,179],"method":[146,180],"evaluated":[148],"on":[149],"two":[150],"distinct":[151],"MMIC":[152],"tasks,":[153],"namely":[154],"polyp":[155],"glaucoma":[158],"classification,":[159],"representing":[160],"scenarios.":[163],"results":[165,175],"are":[166],"compared":[167],"with":[168],"single-modality":[170,184],"methods.":[173,190],"Experimental":[174],"demonstrate":[176],"that":[177,194],"significantly":[181],"outperforms":[182],"all":[183],"approaches":[185],"most":[187],"benchmark":[189],"Further":[191],"analysis":[192],"reveals":[193],"evolved":[196],"models":[197],"can":[198],"effectively":[199],"capture":[200],"unique":[202],"characteristics":[203]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}