{"id":"https://openalex.org/W7126061421","doi":"https://doi.org/10.1109/bibm66473.2025.11357229","title":"Lung Cancer Subtype Classification using Multi-Scale Fusion and Hierarchical Learning","display_name":"Lung Cancer Subtype Classification using Multi-Scale Fusion and Hierarchical Learning","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126061421","doi":"https://doi.org/10.1109/bibm66473.2025.11357229"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11357229","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357229","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":"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/A5124167141","display_name":"Ziyang Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I69356397","display_name":"Xi\u2019an Jiaotong-Liverpool University","ror":"https://ror.org/03zmrmn05","country_code":"CN","type":"education","lineage":["https://openalex.org/I69356397"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziyang Wang","raw_affiliation_strings":["School of AI and Advanced Computing, Xi&#x0027;an Jiaotong - Liverpool University,Suzhou,China"],"affiliations":[{"raw_affiliation_string":"School of AI and Advanced Computing, Xi&#x0027;an Jiaotong - Liverpool University,Suzhou,China","institution_ids":["https://openalex.org/I69356397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108336672","display_name":"Hong Seng Gan","orcid":null},"institutions":[{"id":"https://openalex.org/I69356397","display_name":"Xi\u2019an Jiaotong-Liverpool University","ror":"https://ror.org/03zmrmn05","country_code":"CN","type":"education","lineage":["https://openalex.org/I69356397"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Seng Gan","raw_affiliation_strings":["School of AI and Advanced Computing, Xi&#x0027;an Jiaotong - Liverpool University,Suzhou,China"],"affiliations":[{"raw_affiliation_string":"School of AI and Advanced Computing, Xi&#x0027;an Jiaotong - Liverpool University,Suzhou,China","institution_ids":["https://openalex.org/I69356397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124279493","display_name":"Jiayan Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I69356397","display_name":"Xi\u2019an Jiaotong-Liverpool University","ror":"https://ror.org/03zmrmn05","country_code":"CN","type":"education","lineage":["https://openalex.org/I69356397"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayan Jiang","raw_affiliation_strings":["School of AI and Advanced Computing, Xi&#x0027;an Jiaotong - Liverpool University,Suzhou,China"],"affiliations":[{"raw_affiliation_string":"School of AI and Advanced Computing, Xi&#x0027;an Jiaotong - Liverpool University,Suzhou,China","institution_ids":["https://openalex.org/I69356397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033303302","display_name":"Selen Bayraktaro\u011flu","orcid":"https://orcid.org/0000-0001-9167-9474"},"institutions":[{"id":"https://openalex.org/I41641357","display_name":"Ege University","ror":"https://ror.org/02eaafc18","country_code":"TR","type":"education","lineage":["https://openalex.org/I41641357"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Selen Bayraktaroglu","raw_affiliation_strings":["Ege University,Dept. of Radiology,Izmir,Turkey"],"affiliations":[{"raw_affiliation_string":"Ege University,Dept. of Radiology,Izmir,Turkey","institution_ids":["https://openalex.org/I41641357"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124175210","display_name":"Riries Rulaningtyas","orcid":null},"institutions":[{"id":"https://openalex.org/I205133468","display_name":"Airlangga University","ror":"https://ror.org/04ctejd88","country_code":"ID","type":"education","lineage":["https://openalex.org/I205133468"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Riries Rulaningtyas","raw_affiliation_strings":["Universitas Airlangga,Faculty of Science and Technology,Surabaya,Indonesia"],"affiliations":[{"raw_affiliation_string":"Universitas Airlangga,Faculty of Science and Technology,Surabaya,Indonesia","institution_ids":["https://openalex.org/I205133468"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5124167141"],"corresponding_institution_ids":["https://openalex.org/I69356397"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.74788995,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6117","last_page":"6124"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.4611999988555908,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.4611999988555908,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.28940001130104065,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.07819999754428864,"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/lung-cancer","display_name":"Lung cancer","score":0.5972999930381775},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5324000120162964},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4823000133037567},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.435699999332428},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43479999899864197},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.40139999985694885},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.38999998569488525},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3869999945163727}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6704000234603882},{"id":"https://openalex.org/C2776256026","wikidata":"https://www.wikidata.org/wiki/Q47912","display_name":"Lung cancer","level":2,"score":0.5972999930381775},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.593500018119812},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5324000120162964},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4823000133037567},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4357999861240387},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.435699999332428},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43479999899864197},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.40139999985694885},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.38999998569488525},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3869999945163727},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.3659999966621399},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C2781182431","wikidata":"https://www.wikidata.org/wiki/Q356033","display_name":"Adenocarcinoma","level":3,"score":0.32499998807907104},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2948000133037567},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.29429998993873596},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2903999984264374},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.28619998693466187},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C3019992690","wikidata":"https://www.wikidata.org/wiki/Q92767510","display_name":"Basal cell","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2635999917984009}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11357229","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357229","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":[{"score":0.564247190952301,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2583276680","https://openalex.org/W2598142033","https://openalex.org/W3048173156","https://openalex.org/W3135485367","https://openalex.org/W4285274263","https://openalex.org/W4310282185","https://openalex.org/W4315928876","https://openalex.org/W4383878671","https://openalex.org/W4385437200","https://openalex.org/W4389196705","https://openalex.org/W4399224696","https://openalex.org/W4401416083","https://openalex.org/W4402917106","https://openalex.org/W4405864848","https://openalex.org/W4406147926","https://openalex.org/W4406261573","https://openalex.org/W4407765654","https://openalex.org/W4409262383","https://openalex.org/W4409627776","https://openalex.org/W4410826358","https://openalex.org/W4410907088","https://openalex.org/W4411041914","https://openalex.org/W4411909225","https://openalex.org/W4412414740","https://openalex.org/W4413146579","https://openalex.org/W4413156141","https://openalex.org/W4413754808","https://openalex.org/W7118531506"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"classification":[1,106],"of":[2,16,150],"lung":[3,7,19,56,174],"adenocarcinoma":[4],"(LUAD)":[5],"and":[6,29,41,51,70,96,112,137,155,186,192],"squamous":[8],"cell":[9,18],"carcinoma":[10],"(LUSC),":[11],"the":[12,126,148,182],"two":[13],"major":[14],"subtypes":[15],"non-small":[17],"cancer":[20,57,175],"(NSCLC),":[21],"remains":[22],"challenging":[23],"due":[24],"to":[25,116,158,184,189],"heterogeneous":[26,168],"imaging":[27],"characteristics":[28],"overlapping":[30],"radiological-pathological":[31],"patterns.":[32],"To":[33],"address":[34],"this,":[35],"we":[36],"propose":[37],"M2HCNet,":[38],"a":[39],"Multimodal":[40],"Multiscale":[42],"Hierarchical":[43],"Classification":[44],"Network":[45],"that":[46,130,164],"integrates":[47],"computed":[48],"tomography":[49],"(CT)":[50],"histopathology":[52],"images":[53],"for":[54,172],"robust":[55],"subtype":[58,176],"identification.":[59],"A":[60,104],"multi-scale":[61,151],"feature":[62],"extraction":[63],"module":[64],"captures":[65],"both":[66],"fine-grained":[67],"cellular":[68],"details":[69],"global":[71],"contextual":[72],"structures,":[73],"enabling":[74],"complementary":[75,170],"fusion":[76],"across":[77],"modalities.":[78],"The":[79],"extracted":[80],"features":[81],"are":[82],"then":[83],"aligned":[84],"using":[85],"an":[86],"optimal":[87],"transport-based":[88],"contrastive":[89],"alignment":[90],"strategy,":[91],"which":[92],"reduces":[93],"distributional":[94],"discrepancies":[95],"enhances":[97],"cross-modal":[98,153],"consistency":[99],"under":[100],"weakly":[101],"paired":[102],"conditions.":[103],"hierarchical":[105,156],"mechanism":[107],"further":[108],"models":[109],"inter-class":[110],"relationships":[111],"coarse-to-fine":[113],"label":[114],"dependencies":[115],"improve":[117],"discrimination":[118],"between":[119],"closely":[120],"related":[121],"subtypes.":[122],"Experiments":[123],"conducted":[124],"on":[125],"TCGA-LUAD/LUSC":[127],"cohort":[128],"demonstrate":[129],"M2HCNet":[131,165],"achieves":[132],"93.8%":[133],"accuracy,":[134],"91.9%":[135],"F1-score,":[136],"95.5%":[138],"AUC,":[139],"outperforming":[140],"ten":[141],"recent":[142],"state-of-the-art":[143],"baselines.":[144],"Ablation":[145],"studies":[146],"confirm":[147],"contributions":[149],"fusion,":[152],"alignment,":[154],"learning":[157],"overall":[159],"performance.":[160],"These":[161],"findings":[162],"suggest":[163],"effectively":[166],"leverages":[167],"yet":[169],"modalities":[171],"reliable":[173],"classification.":[177],"Future":[178],"work":[179],"will":[180],"extend":[181],"framework":[183],"patient-matched":[185],"multi-institutional":[187],"datasets":[188],"enhance":[190],"generalization":[191],"clinical":[193],"applicability.":[194]},"counts_by_year":[],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2026-01-30T00:00:00"}
