{"id":"https://openalex.org/W4410295310","doi":"https://doi.org/10.1109/isbi60581.2025.10981001","title":"Longmambattn: A Novel Architecture for Enhanced Breast Cancer Risk Prediction Using Variable-Length Longitudinal Mammograms","display_name":"Longmambattn: A Novel Architecture for Enhanced Breast Cancer Risk Prediction Using Variable-Length Longitudinal Mammograms","publication_year":2025,"publication_date":"2025-04-14","ids":{"openalex":"https://openalex.org/W4410295310","doi":"https://doi.org/10.1109/isbi60581.2025.10981001"},"language":"en","primary_location":{"id":"doi:10.1109/isbi60581.2025.10981001","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi60581.2025.10981001","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)","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/A5101466459","display_name":"Zhengbo Zhou","orcid":"https://orcid.org/0000-0002-9085-9403"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengbo Zhou","raw_affiliation_strings":["University of Pittsburgh,Intelligent Systems Program,Pittsburgh,PA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pittsburgh,Intelligent Systems Program,Pittsburgh,PA,USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074743495","display_name":"Dooman Arefan","orcid":"https://orcid.org/0000-0001-9679-0438"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dooman Arefan","raw_affiliation_strings":["University of Pittsburgh,Department of Radiology,Pittsburgh,PA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pittsburgh,Department of Radiology,Pittsburgh,PA,USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054344119","display_name":"Margarita L. Zuley","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Margarita Zuley","raw_affiliation_strings":["University of Pittsburgh,Intelligent Systems Program,Pittsburgh,PA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pittsburgh,Intelligent Systems Program,Pittsburgh,PA,USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028928157","display_name":"Jules H. Sumkin","orcid":"https://orcid.org/0000-0003-1124-9445"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jules Sumkin","raw_affiliation_strings":["University of Pittsburgh,Intelligent Systems Program,Pittsburgh,PA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pittsburgh,Intelligent Systems Program,Pittsburgh,PA,USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028418236","display_name":"Shandong Wu","orcid":"https://orcid.org/0000-0002-0770-2203"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shandong Wu","raw_affiliation_strings":["University of Pittsburgh,Intelligent Systems Program,Pittsburgh,PA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pittsburgh,Intelligent Systems Program,Pittsburgh,PA,USA","institution_ids":["https://openalex.org/I170201317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"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":0.04151415,"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":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9865999817848206,"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":0.9865999817848206,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.696449875831604},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.5391550064086914},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5342769622802734},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5013506412506104},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.48998942971229553},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.39389172196388245},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.23042234778404236},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21823596954345703},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.1957886517047882}],"concepts":[{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.696449875831604},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5391550064086914},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5342769622802734},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5013506412506104},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.48998942971229553},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.39389172196388245},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.23042234778404236},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21823596954345703},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.1957886517047882},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi60581.2025.10981001","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi60581.2025.10981001","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.6600000262260437,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G4276999142","display_name":null,"funder_award_id":"2115082,2138259,2138286,2138307,2137603,2138296","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1549906179","https://openalex.org/W2986544402","https://openalex.org/W3138516171","https://openalex.org/W4286567656","https://openalex.org/W4387211800","https://openalex.org/W4393404592","https://openalex.org/W4394007483","https://openalex.org/W4401629450","https://openalex.org/W4403089078","https://openalex.org/W6765458459","https://openalex.org/W6803444062","https://openalex.org/W6859298233"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W1514924336","https://openalex.org/W2002967116","https://openalex.org/W2024400191","https://openalex.org/W4405112912","https://openalex.org/W2024878248","https://openalex.org/W2375584271","https://openalex.org/W1997105855","https://openalex.org/W2379981957","https://openalex.org/W1976069075"],"abstract_inverted_index":{"Recent":[0],"advancements":[1],"in":[2,9,20,33,98],"deep":[3],"learning":[4],"have":[5],"shown":[6],"significant":[7],"potential":[8],"predicting":[10,99],"breast":[11,64,142],"cancer":[12,65,101,143],"risk":[13,26,66],"from":[14,80],"mammograms.":[15],"While":[16],"leveraging":[17],"longitudinal":[18,132],"changes":[19,73],"mammograms":[21,75,121,133],"is":[22],"crucial":[23],"for":[24,141],"accurate":[25],"prediction,":[27],"existing":[28],"models":[29,70,118],"often":[30],"face":[31],"limitations":[32],"capturing":[34],"these":[35,48],"temporal":[36,72],"relationships":[37],"effectively,":[38],"and":[39],"they":[40],"tend":[41],"to":[42,57,82,137],"be":[43],"computationally":[44],"intensive.":[45],"To":[46],"address":[47],"challenges,":[49],"we":[50],"introduce":[51],"LongMambAttn,":[52],"a":[53],"novel":[54],"architecture":[55],"designed":[56],"handle":[58],"variable-length,":[59],"multitemporal":[60],"mammograms,":[61],"thereby":[62],"enhancing":[63],"prediction":[67],"accuracy.":[68],"LongMambAttn":[69,135],"the":[71,109],"of":[74,90],"taken":[76,122],"over":[77],"periods":[78],"ranging":[79],"1":[81],"8":[83],"years.":[84],"In":[85],"an":[86],"internal":[87],"case-control":[88],"dataset":[89],"590":[91],"patients,":[92],"our":[93],"model":[94],"demonstrates":[95],"superior":[96],"performance":[97],"future":[100],"incidence,":[102],"surpassing":[103],"methods":[104],"that":[105,119,130],"rely":[106],"only":[107],"on":[108],"most":[110],"recent":[111],"prior":[112],"mammogram":[113],"as":[114,116],"well":[115],"other":[117],"incorporate":[120],"at":[123],"varying":[124],"time":[125],"intervals.":[126],"Our":[127],"results":[128],"show":[129],"incorporating":[131],"via":[134],"leads":[136],"improved":[138],"predictive":[139],"accuracy":[140],"risk.":[144]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
