{"id":"https://openalex.org/W7126106314","doi":"https://doi.org/10.1109/bibm66473.2025.11356637","title":"Mitigating Class Imbalance in Colorectal Histopathological Image Classification Using Data Synthesis and Adaptive Loss","display_name":"Mitigating Class Imbalance in Colorectal Histopathological Image Classification Using Data Synthesis and Adaptive Loss","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126106314","doi":"https://doi.org/10.1109/bibm66473.2025.11356637"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356637","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356637","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103655788","display_name":"Li Yuan","orcid":"https://orcid.org/0009-0007-0129-7669"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingling Yuan","raw_affiliation_strings":["Northeastern University,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,Shenyang,China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124190750","display_name":"Hao Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hao Xu","raw_affiliation_strings":["University of Sydney,Sydney,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Sydney,Sydney,Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hongzan Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I91656880","display_name":"China Medical University","ror":"https://ror.org/032d4f246","country_code":"CN","type":"education","lineage":["https://openalex.org/I91656880"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongzan Sun","raw_affiliation_strings":["China Medical University,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Medical University,Shenyang,China","institution_ids":["https://openalex.org/I91656880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101745652","display_name":"Siyan Liu","orcid":"https://orcid.org/0000-0001-9091-4997"},"institutions":[{"id":"https://openalex.org/I91656880","display_name":"China Medical University","ror":"https://ror.org/032d4f246","country_code":"CN","type":"education","lineage":["https://openalex.org/I91656880"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyan Li","raw_affiliation_strings":["China Medical University,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Medical University,Shenyang,China","institution_ids":["https://openalex.org/I91656880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124218061","display_name":"Xueyan Bai","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueyan Bai","raw_affiliation_strings":["Northeastern University,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,Shenyang,China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124256873","display_name":"Marcin Grzegorzek","orcid":null},"institutions":[{"id":"https://openalex.org/I2802859012","display_name":"Becker College","ror":"https://ror.org/00vn6kg36","country_code":"US","type":"education","lineage":["https://openalex.org/I2802859012"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marcin Grzegorzek","raw_affiliation_strings":["University of L&#x00FC;beck,L&#x00FC;beck,German"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of L&#x00FC;beck,L&#x00FC;beck,German","institution_ids":["https://openalex.org/I2802859012"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124197153","display_name":"Chen Li","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Li","raw_affiliation_strings":["Northeastern University,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University,Shenyang,China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"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":0.66264786,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6822","last_page":"6829"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9397000074386597,"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/T10862","display_name":"AI in cancer detection","score":0.9397000074386597,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.012400000356137753,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.007000000216066837,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5899999737739563},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5759000182151794},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5716000199317932},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5623000264167786},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5529000163078308},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49000000953674316},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4542999863624573},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4129999876022339}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6261000037193298},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6244999766349792},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5899999737739563},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5759000182151794},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5716000199317932},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5623000264167786},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5529000163078308},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49000000953674316},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4542999863624573},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4129999876022339},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3808000087738037},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.37549999356269836},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C526805850","wikidata":"https://www.wikidata.org/wiki/Q188874","display_name":"Colorectal cancer","level":3,"score":0.2791000008583069},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.2718000113964081},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C193519340","wikidata":"https://www.wikidata.org/wiki/Q891179","display_name":"Data loss","level":2,"score":0.2612000107765198}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356637","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356637","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2970193089","display_name":null,"funder_award_id":"82220108007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7954749856","display_name":null,"funder_award_id":"GZR20240330","funder_id":"https://openalex.org/F4320324301","funder_display_name":"China Medical University"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324301","display_name":"China Medical University","ror":"https://ror.org/032d4f246"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2344480160","https://openalex.org/W2618999197","https://openalex.org/W2797558164","https://openalex.org/W2963351448","https://openalex.org/W3000722911","https://openalex.org/W3003607530","https://openalex.org/W3005927567","https://openalex.org/W3012641931","https://openalex.org/W3093668614","https://openalex.org/W3122741953","https://openalex.org/W3152579480","https://openalex.org/W3209549170","https://openalex.org/W4200573592","https://openalex.org/W4293718652","https://openalex.org/W4307644744","https://openalex.org/W4313837151","https://openalex.org/W4317934666","https://openalex.org/W4321201254","https://openalex.org/W4362500858","https://openalex.org/W4385380878","https://openalex.org/W4386187846","https://openalex.org/W4391690902","https://openalex.org/W4401344535","https://openalex.org/W4402445510"],"related_works":[],"abstract_inverted_index":{"Histopathological":[0],"image":[1,51],"classification":[2,52],"in":[3],"colorectal":[4],"cancer":[5,127],"(CRC)":[6],"is":[7],"hindered":[8],"by":[9],"class":[10],"imbalance,":[11],"where":[12],"limited":[13],"data":[14,45],"for":[15,70],"some":[16],"classes":[17,32],"and":[18,47,89,113,125],"overlapping":[19],"features":[20],"lead":[21],"to":[22,28,66,83],"degraded":[23],"performance.":[24],"Traditional":[25],"methods":[26],"struggle":[27],"adequately":[29],"augment":[30],"minority":[31],"or":[33],"resolve":[34],"these":[35,39,116],"uncertainties.":[36],"To":[37],"alleviate":[38],"problems,":[40],"we":[41],"propose":[42],"a":[43,59],"novel":[44],"synthesis":[46],"adaptive":[48,79],"loss-based":[49],"histopathological":[50],"framework":[53],"that":[54],"integrates":[55],"two":[56],"components:":[57],"1)":[58],"global":[60],"context":[61],"generative":[62],"adversarial":[63],"network":[64],"(GCGAN)":[65],"generate":[67],"realistic":[68],"images":[69],"under-represented":[71],"classes,":[72],"thereby":[73],"enriching":[74],"dataset":[75,98],"diversity;":[76],"2)":[77],"an":[78],"focal":[80],"loss":[81,87],"(AFL)":[82],"dynamically":[84],"adjust":[85],"the":[86,96,100],"function":[88],"mitigate":[90],"feature":[91],"overlap.":[92],"Extensive":[93],"experiments":[94],"on":[95,122],"CRC":[97],"demonstrate":[99],"effectiveness":[101],"of":[102],"our":[103],"approach,":[104],"outperforming":[105],"other":[106],"state-of-the-art":[107],"(SOTA)":[108],"methods.":[109],"Additionally,":[110],"combining":[111],"GCGAN":[112],"AFL":[114],"benefits":[115],"SOTA":[117],"methods,":[118],"with":[119],"performance":[120],"improvements":[121],"cervical":[123],"(CC)":[124],"breast":[126],"(BC)":[128],"datasets.":[129]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-01-30T00:00:00"}
