{"id":"https://openalex.org/W2980153903","doi":"https://doi.org/10.1109/embc.2019.8857030","title":"A Reliable Multi-classifier Multi-objective Model for Predicting Recurrence in Triple Negative Breast Cancer","display_name":"A Reliable Multi-classifier Multi-objective Model for Predicting Recurrence in Triple Negative Breast Cancer","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2980153903","doi":"https://doi.org/10.1109/embc.2019.8857030","mag":"2980153903","pmid":"https://pubmed.ncbi.nlm.nih.gov/31946334"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2019.8857030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2019.8857030","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","pubmed"],"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/A5100329852","display_name":"Xi Chen","orcid":"https://orcid.org/0000-0001-7094-6748"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Chen","raw_affiliation_strings":["School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi\u2019an, Shaanxi, China","School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi\u2019an, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100785328","display_name":"Zhiguo Zhou","orcid":"https://orcid.org/0000-0003-4031-3178"},"institutions":[{"id":"https://openalex.org/I867280407","display_name":"The University of Texas Southwestern Medical Center","ror":"https://ror.org/05byvp690","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I867280407"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiguo Zhou","raw_affiliation_strings":["Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA","institution_ids":["https://openalex.org/I867280407"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102813406","display_name":"K. Thomas","orcid":"https://orcid.org/0000-0002-9183-3432"},"institutions":[{"id":"https://openalex.org/I867280407","display_name":"The University of Texas Southwestern Medical Center","ror":"https://ror.org/05byvp690","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I867280407"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kimberly Thomas","raw_affiliation_strings":["University of Texas Southwestern Medical Center, Dallas, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Texas Southwestern Medical Center, Dallas, TX, USA","institution_ids":["https://openalex.org/I867280407"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057027370","display_name":"Michael R. Folkert","orcid":"https://orcid.org/0000-0003-3062-9793"},"institutions":[{"id":"https://openalex.org/I867280407","display_name":"The University of Texas Southwestern Medical Center","ror":"https://ror.org/05byvp690","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I867280407"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Folkert","raw_affiliation_strings":["Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA","institution_ids":["https://openalex.org/I867280407"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006527256","display_name":"Nathan Kim","orcid":"https://orcid.org/0000-0002-0503-0263"},"institutions":[{"id":"https://openalex.org/I867280407","display_name":"The University of Texas Southwestern Medical Center","ror":"https://ror.org/05byvp690","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I867280407"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nathan Kim","raw_affiliation_strings":["Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA","institution_ids":["https://openalex.org/I867280407"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000962617","display_name":"Asal Rahimi","orcid":"https://orcid.org/0000-0002-2762-5049"},"institutions":[{"id":"https://openalex.org/I867280407","display_name":"The University of Texas Southwestern Medical Center","ror":"https://ror.org/05byvp690","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I867280407"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Asal Rahimi","raw_affiliation_strings":["Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA","institution_ids":["https://openalex.org/I867280407"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100378618","display_name":"Jing Wang","orcid":"https://orcid.org/0000-0002-9272-5628"},"institutions":[{"id":"https://openalex.org/I867280407","display_name":"The University of Texas Southwestern Medical Center","ror":"https://ror.org/05byvp690","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I867280407"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jing Wang","raw_affiliation_strings":["Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA","institution_ids":["https://openalex.org/I867280407"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.025,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.95611398,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"2019","issue":null,"first_page":"2182","last_page":"2185"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9950000047683716,"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"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.989300012588501,"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/classifier","display_name":"Classifier (UML)","score":0.7543087601661682},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6801400184631348},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.6760818958282471},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5839398503303528},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5818408131599426},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.48428434133529663},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3629879355430603},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.14377251267433167},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.13748785853385925}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7543087601661682},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6801400184631348},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.6760818958282471},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5839398503303528},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5818408131599426},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.48428434133529663},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3629879355430603},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.14377251267433167},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.13748785853385925},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009364","descriptor_name":"Neoplasm Recurrence, Local","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009364","descriptor_name":"Neoplasm Recurrence, Local","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009364","descriptor_name":"Neoplasm Recurrence, Local","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012372","descriptor_name":"ROC Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012372","descriptor_name":"ROC Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012372","descriptor_name":"ROC Curve","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D064726","descriptor_name":"Triple Negative Breast Neoplasms","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D064726","descriptor_name":"Triple Negative Breast Neoplasms","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D064726","descriptor_name":"Triple Negative Breast Neoplasms","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc.2019.8857030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2019.8857030","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:31946334","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31946334","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.7599999904632568}],"awards":[{"id":"https://openalex.org/G2193445388","display_name":null,"funder_award_id":"R01EB020366","funder_id":"https://openalex.org/F4320337363","funder_display_name":"National Institute of Biomedical Imaging and Bioengineering"}],"funders":[{"id":"https://openalex.org/F4320337363","display_name":"National Institute of Biomedical Imaging and Bioengineering","ror":"https://ror.org/00372qc85"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W195533127","https://openalex.org/W1995224853","https://openalex.org/W2049337423","https://openalex.org/W2114541394","https://openalex.org/W2118605519","https://openalex.org/W2120160105","https://openalex.org/W2170602872","https://openalex.org/W2461805626","https://openalex.org/W2496177076","https://openalex.org/W2530103281","https://openalex.org/W2612594530","https://openalex.org/W2782881162","https://openalex.org/W2806419994","https://openalex.org/W2811120089","https://openalex.org/W2911188335"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W2921036759","https://openalex.org/W3158004940","https://openalex.org/W2001652754","https://openalex.org/W2549006548","https://openalex.org/W4214932115","https://openalex.org/W2807311372","https://openalex.org/W3043252291","https://openalex.org/W3174196512","https://openalex.org/W2379065761"],"abstract_inverted_index":{"Recurrence":[0],"is":[1,20,27,60],"a":[2,28,47,66,72,81,134],"significant":[3],"prognostic":[4],"factor":[5],"in":[6],"patients":[7],"with":[8,146],"triple":[9],"negative":[10],"breast":[11],"cancer,":[12],"and":[13,44,93,97,149,158,168],"the":[14,63,100,108,117,128,138,155],"ability":[15],"to":[16,75,122],"accurately":[17],"predict":[18],"it":[19],"essential":[21],"for":[22,31,115],"treatment":[23],"optimization.":[24],"Machine":[25],"learning":[26],"preferred":[29],"strategy":[30],"recurrence":[32,86],"prediction.":[33],"Most":[34],"current":[35],"predictive":[36,87,135],"models":[37],"are":[38,54],"built":[39],"based":[40],"on":[41],"single":[42,48,67],"classifier":[43,121],"trained":[45],"through":[46],"objective.":[49],"However,":[50],"since":[51],"many":[52],"classifiers":[53],"available,":[55],"selecting":[56],"an":[57],"optimal":[58],"model":[59,77],"challenging.":[61],"On":[62],"other":[64,164],"hand,":[65],"objective":[68,102],"may":[69],"not":[70],"be":[71],"good":[73],"measure":[74],"guide":[76],"training.":[78,106],"We":[79],"proposed":[80,129],"new":[82,90],"multi-classifier":[83],"multi-objective":[84],"(MCMO)":[85],"model.":[88],"Specifically,":[89],"similarity-based":[91],"sensitivity":[92,148],"specificity":[94],"were":[95],"defined":[96],"considered":[98],"as":[99],"two":[101],"functions":[103],"simultaneously":[104],"during":[105],"Also":[107],"evidential":[109],"reasoning":[110],"(ER)":[111],"approach":[112],"was":[113],"used":[114,166],"fusing":[116],"output":[118],"of":[119,144],"each":[120],"obtain":[123],"more":[124,160],"reliable":[125,161],"outcome.":[126],"Using":[127],"MCMO":[130,152],"model,":[131],"we":[132],"achieved":[133],"area":[136],"under":[137],"receiver":[139],"operating":[140],"characteristic":[141],"curve":[142],"(AUC)":[143],"0.9":[145],"balanced":[147],"specificity.":[150],"Furthermore,":[151],"outperformed":[153],"all":[154],"individual":[156],"classifiers,":[157],"yielded":[159],"results":[162],"than":[163],"commonly":[165],"optimization":[167],"fusion":[169],"methods.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2019-10-18T00:00:00"}