{"id":"https://openalex.org/W7155853800","doi":"https://doi.org/10.1109/access.2026.3687751","title":"Multi-View Hypercomplex Learning for Breast Cancer Screening","display_name":"Multi-View Hypercomplex Learning for Breast Cancer Screening","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7155853800","doi":"https://doi.org/10.1109/access.2026.3687751"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3687751","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3687751","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3687751","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053390099","display_name":"Eleonora Lopez","orcid":"https://orcid.org/0000-0002-4107-663X"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Eleonora Lopez","raw_affiliation_strings":["Department of Information Engineering, Electronics, and Telecommunications (DIET), Sapienza University of Rome, Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0002-4107-663X","affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Electronics, and Telecommunications (DIET), Sapienza University of Rome, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003606065","display_name":"Eleonora Grassucci","orcid":"https://orcid.org/0000-0003-4626-4506"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Eleonora Grassucci","raw_affiliation_strings":["Department of Information Engineering, Electronics, and Telecommunications (DIET), Sapienza University of Rome, Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0003-4626-4506","affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Electronics, and Telecommunications (DIET), Sapienza University of Rome, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019647783","display_name":"Danilo Comminiello","orcid":"https://orcid.org/0000-0003-4067-4504"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Danilo Comminiello","raw_affiliation_strings":["Department of Information Engineering, Electronics, and Telecommunications (DIET), Sapienza University of Rome, Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0003-4067-4504","affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Electronics, and Telecommunications (DIET), Sapienza University of Rome, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I861853513"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.49293751,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"66526","last_page":"66538"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9153000116348267,"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":0.9153000116348267,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.004800000227987766,"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/T12994","display_name":"Infrared Thermography in Medicine","score":0.004699999932199717,"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/hypercomplex-number","display_name":"Hypercomplex number","score":0.7093999981880188},{"id":"https://openalex.org/keywords/breast-cancer-screening","display_name":"Breast cancer screening","score":0.5472999811172485},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.5382000207901001},{"id":"https://openalex.org/keywords/breast-screening","display_name":"Breast screening","score":0.3384000062942505},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.3066999912261963}],"concepts":[{"id":"https://openalex.org/C203249530","wikidata":"https://www.wikidata.org/wiki/Q837414","display_name":"Hypercomplex number","level":3,"score":0.7093999981880188},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.6764000058174133},{"id":"https://openalex.org/C143998085","wikidata":"https://www.wikidata.org/wiki/Q162555","display_name":"Oncology","level":1,"score":0.5557000041007996},{"id":"https://openalex.org/C2778491387","wikidata":"https://www.wikidata.org/wiki/Q17011492","display_name":"Breast cancer screening","level":5,"score":0.5472999811172485},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.5382000207901001},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.49889999628067017},{"id":"https://openalex.org/C2985394991","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Breast screening","level":5,"score":0.3384000062942505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3070000112056732},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.3066999912261963},{"id":"https://openalex.org/C2776463041","wikidata":"https://www.wikidata.org/wiki/Q3044843","display_name":"Cancer screening","level":3,"score":0.2994999885559082},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.2946000099182129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2892000079154968},{"id":"https://openalex.org/C3020067899","wikidata":"https://www.wikidata.org/wiki/Q1163564","display_name":"Screening test","level":2,"score":0.28040000796318054}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3687751","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3687751","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5dc7dd3e1c824fa8b47258a05b100d3a","is_oa":true,"landing_page_url":"https://doaj.org/article/5dc7dd3e1c824fa8b47258a05b100d3a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 66526-66538 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3687751","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3687751","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Radiologists":[0],"interpret":[1],"mammography":[2],"exams":[3,85],"by":[4,36],"jointly":[5],"analyzing":[6],"all":[7],"four":[8],"views,":[9],"as":[10,120],"correlations":[11],"among":[12],"them":[13],"are":[14,33,136],"crucial":[15],"for":[16,56,83,93,98],"an":[17],"accurate":[18],"diagnosis.":[19],"Recent":[20],"methods":[21],"have":[22],"employed":[23],"dedicated":[24],"fusion":[25],"blocks":[26],"to":[27,69],"capture":[28,75],"such":[29,119],"dependencies,":[30],"but":[31],"these":[32,46],"often":[34],"hindered":[35],"view":[37],"dominance,":[38],"training":[39],"instability,":[40],"and":[41,86,95,117,126,133],"computational":[42],"overhead.":[43],"To":[44],"address":[45],"challenges,":[47],"we":[48],"introducemulti-view":[49],"hypercomplex":[50,64,70],"learning,":[51],"a":[52],"novel":[53],"learning":[54],"paradigm":[55],"multi-view":[57,109],"breast":[58],"cancer":[59],"classification":[60,122],"based":[61],"on":[62],"parameterized":[63],"neural":[65],"networks":[66],"(PHNNs).":[67],"Thanks":[68],"algebra,":[71],"our":[72,104],"models":[73,135],"intrinsically":[74],"both":[76],"intra-and":[77],"inter-view":[78],"relations.":[79],"We":[80],"propose":[81],"PHResNets":[82],"two-view":[84],"two":[87],"complementary":[88],"four-view":[89],"architectures:":[90],"PHYBOnet,":[91],"optimized":[92,97],"efficiency,":[94],"PHYSEnet,":[96],"accuracy.":[99],"Extensive":[100],"experiments":[101],"demonstrate":[102],"that":[103],"approach":[105],"consistently":[106],"outperforms":[107],"state-of-the-art":[108],"models,":[110],"while":[111],"also":[112],"generalizing":[113],"across":[114],"radiographic":[115],"modalities":[116],"tasks":[118],"disease":[121],"from":[123],"chest":[124],"X-rays":[125],"multimodal":[127],"brain":[128],"tumor":[129],"segmentation.":[130],"Full":[131],"code":[132],"pretrained":[134],"available":[137],"at":[138],"https:":[139],"//github.com/ispamm/PHBreast.":[140]},"counts_by_year":[],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2026-04-28T00:00:00"}
