{"id":"https://openalex.org/W4388117862","doi":"https://doi.org/10.23919/eusipco58844.2023.10290122","title":"Predicting Ovarian Cancer with Machine Learning: Integrating Clinical and Genetic Data","display_name":"Predicting Ovarian Cancer with Machine Learning: Integrating Clinical and Genetic Data","publication_year":2023,"publication_date":"2023-09-04","ids":{"openalex":"https://openalex.org/W4388117862","doi":"https://doi.org/10.23919/eusipco58844.2023.10290122"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco58844.2023.10290122","is_oa":false,"landing_page_url":"http://dx.doi.org/10.23919/eusipco58844.2023.10290122","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 31st European Signal Processing Conference (EUSIPCO)","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/A5092996387","display_name":"Ismael G\u00f3mez-Talal","orcid":"https://orcid.org/0000-0003-4673-8193"},"institutions":[{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Ismael G\u00f3mez-Talal","raw_affiliation_strings":["Universidad Rey Juan Carlos,Dept. Sig. Theory Comms.,Fuenlabrada,Madrid,Spain","Dept. Sig. Theory Comms., Universidad Rey Juan Carlos, Fuenlabrada, Madrid, Spain"],"raw_orcid":"https://orcid.org/0000-0003-4673-8193","affiliations":[{"raw_affiliation_string":"Universidad Rey Juan Carlos,Dept. Sig. Theory Comms.,Fuenlabrada,Madrid,Spain","institution_ids":["https://openalex.org/I182083151"]},{"raw_affiliation_string":"Dept. Sig. Theory Comms., Universidad Rey Juan Carlos, Fuenlabrada, Madrid, Spain","institution_ids":["https://openalex.org/I182083151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047341028","display_name":"Ar\u00e1ntzazu Barqu\u00edn","orcid":"https://orcid.org/0000-0002-3701-0347"},"institutions":[{"id":"https://openalex.org/I4210137474","display_name":"Hospital Universitario HM Sanchinarro","ror":"https://ror.org/04jep6391","country_code":"ES","type":"healthcare","lineage":["https://openalex.org/I4210122338","https://openalex.org/I4210137474"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Arantzazu Barqu\u00edn","raw_affiliation_strings":["Unit of Gyn., Genitour. Skin Tum. Hospital HM Sanchinarro,Madrid,Spain","Unit of Gyn., Genitour. Skin Tum. Hospital HM Sanchinarro, Madrid, Spain"],"raw_orcid":"https://orcid.org/0000-0002-3701-0347","affiliations":[{"raw_affiliation_string":"Unit of Gyn., Genitour. Skin Tum. Hospital HM Sanchinarro,Madrid,Spain","institution_ids":["https://openalex.org/I4210137474"]},{"raw_affiliation_string":"Unit of Gyn., Genitour. Skin Tum. Hospital HM Sanchinarro, Madrid, Spain","institution_ids":["https://openalex.org/I4210137474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082609425","display_name":"Luis Bote-Curiel","orcid":"https://orcid.org/0000-0001-8845-2834"},"institutions":[{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Luis Bote-Curiel","raw_affiliation_strings":["Universidad Rey Juan Carlos,Dept. Sig. Theory Comms.,Fuenlabrada,Madrid,Spain","Dept. Sig. Theory Comms., Universidad Rey Juan Carlos, Fuenlabrada, Madrid, Spain"],"raw_orcid":"https://orcid.org/0000-0001-8845-2834","affiliations":[{"raw_affiliation_string":"Universidad Rey Juan Carlos,Dept. Sig. Theory Comms.,Fuenlabrada,Madrid,Spain","institution_ids":["https://openalex.org/I182083151"]},{"raw_affiliation_string":"Dept. Sig. Theory Comms., Universidad Rey Juan Carlos, Fuenlabrada, Madrid, Spain","institution_ids":["https://openalex.org/I182083151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074730628","display_name":"M\u00f3nica Yag\u00fce-Fern\u00e1ndez","orcid":"https://orcid.org/0000-0001-9438-5703"},"institutions":[{"id":"https://openalex.org/I4210137474","display_name":"Hospital Universitario HM Sanchinarro","ror":"https://ror.org/04jep6391","country_code":"ES","type":"healthcare","lineage":["https://openalex.org/I4210122338","https://openalex.org/I4210137474"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"M\u00f3nica Yag\u00fce-Fern\u00e1ndez","raw_affiliation_strings":["Unit of Gyn., Genitour. Skin Tum. Hospital HM Sanchinarro,Madrid,Spain","Unit of Gyn., Genitour. Skin Tum. Hospital HM Sanchinarro, Madrid, Spain"],"raw_orcid":"https://orcid.org/0000-0001-9438-5703","affiliations":[{"raw_affiliation_string":"Unit of Gyn., Genitour. Skin Tum. Hospital HM Sanchinarro,Madrid,Spain","institution_ids":["https://openalex.org/I4210137474"]},{"raw_affiliation_string":"Unit of Gyn., Genitour. Skin Tum. Hospital HM Sanchinarro, Madrid, Spain","institution_ids":["https://openalex.org/I4210137474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051286582","display_name":"Jos\u00e9 Luis Rojo\u2010\u00c1lvarez","orcid":"https://orcid.org/0000-0003-0426-8912"},"institutions":[{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jos\u00e9 Luis Raja-\u00c1lvarez","raw_affiliation_strings":["Universidad Rey Juan Carlos,Dept. Sig. Theory Comms.,Fuenlabrada,Madrid,Spain","Dept. Sig. Theory Comms., Universidad Rey Juan Carlos, Fuenlabrada, Madrid, Spain"],"raw_orcid":"https://orcid.org/0000-0003-0426-8912","affiliations":[{"raw_affiliation_string":"Universidad Rey Juan Carlos,Dept. Sig. Theory Comms.,Fuenlabrada,Madrid,Spain","institution_ids":["https://openalex.org/I182083151"]},{"raw_affiliation_string":"Dept. Sig. Theory Comms., Universidad Rey Juan Carlos, Fuenlabrada, Madrid, Spain","institution_ids":["https://openalex.org/I182083151"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004741487","display_name":"Jes\u00fas Garc\u00eda-Don\u00e1s","orcid":"https://orcid.org/0000-0001-7731-3601"},"institutions":[{"id":"https://openalex.org/I4210137474","display_name":"Hospital Universitario HM Sanchinarro","ror":"https://ror.org/04jep6391","country_code":"ES","type":"healthcare","lineage":["https://openalex.org/I4210122338","https://openalex.org/I4210137474"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jes\u00fas Garc\u00eda-Don\u00e1s","raw_affiliation_strings":["Unit of Gyn., Genitour. Skin Tum. Hospital HM Sanchinarro,Madrid,Spain","Unit of Gyn., Genitour. Skin Tum. Hospital HM Sanchinarro, Madrid, Spain"],"raw_orcid":"https://orcid.org/0000-0001-7731-3601","affiliations":[{"raw_affiliation_string":"Unit of Gyn., Genitour. Skin Tum. Hospital HM Sanchinarro,Madrid,Spain","institution_ids":["https://openalex.org/I4210137474"]},{"raw_affiliation_string":"Unit of Gyn., Genitour. Skin Tum. Hospital HM Sanchinarro, Madrid, Spain","institution_ids":["https://openalex.org/I4210137474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5092996387"],"corresponding_institution_ids":["https://openalex.org/I182083151"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.50265584,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1160","last_page":"1164"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"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/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"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/T10550","display_name":"Ovarian cancer diagnosis and treatment","score":0.9876000285148621,"subfield":{"id":"https://openalex.org/subfields/2743","display_name":"Reproductive 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/T10594","display_name":"Genetic and phenotypic traits in livestock","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"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"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.9326796531677246},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6842389106750488},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.682611346244812},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6700166463851929},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5838963389396667},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.5000531673431396},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.44249674677848816},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4344463050365448},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4215722978115082},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.18935516476631165},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.1357901394367218},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0960259735584259},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09227308630943298},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.08712276816368103}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9326796531677246},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6842389106750488},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.682611346244812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6700166463851929},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5838963389396667},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.5000531673431396},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.44249674677848816},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4344463050365448},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4215722978115082},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.18935516476631165},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.1357901394367218},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0960259735584259},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09227308630943298},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.08712276816368103},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco58844.2023.10290122","is_oa":false,"landing_page_url":"http://dx.doi.org/10.23919/eusipco58844.2023.10290122","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 31st European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W20405322","https://openalex.org/W1678356000","https://openalex.org/W1976526581","https://openalex.org/W2010441486","https://openalex.org/W2085770564","https://openalex.org/W2101234009","https://openalex.org/W2106393550","https://openalex.org/W2113242816","https://openalex.org/W2151511400","https://openalex.org/W2153635508","https://openalex.org/W2295598076","https://openalex.org/W2332185934","https://openalex.org/W2484065175","https://openalex.org/W2529222270","https://openalex.org/W2786672974","https://openalex.org/W3049190448","https://openalex.org/W4294541781","https://openalex.org/W6675354045","https://openalex.org/W6728147186","https://openalex.org/W6748816842"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4361193272","https://openalex.org/W2963326959","https://openalex.org/W4388685194","https://openalex.org/W4312407344","https://openalex.org/W4387145687"],"abstract_inverted_index":{"Ovarian":[0],"cancer":[1],"(OC)":[2],"is":[3],"a":[4,9],"deadly":[5],"disease":[6,166],"that":[7,116,143],"affects":[8],"large":[10],"number":[11],"of":[12,25,31,40,54,63,72,88,122,130,133,146],"women":[13],"worldwide.":[14],"Machine":[15],"Learning":[16],"(ML)":[17],"models":[18,33,76,99,118],"can":[19,160],"help":[20,161],"in":[21,135],"the":[22,29,43,89,103,109,120,128,131,139,144,154,165],"early":[23],"detection":[24],"this":[26,50,94],"disease,":[27],"however,":[28],"use":[30,71],"these":[32],"may":[34],"be":[35],"limited":[36],"by":[37,157],"their":[38,47],"lack":[39],"interpretability":[41,87],"and":[42,67,79,102,106,125,151,168],"difficulty":[44],"to":[45,163],"evaluate":[46],"performance.":[48],"In":[49],"work,":[51],"five":[52,90],"types":[53,62],"datasets":[55],"were":[56,100,111],"used,":[57],"employing":[58],"clinical":[59,123],"features,":[60,66],"different":[61,147],"coding":[64,129],"genomic":[65],"combining":[68],"both.":[69],"The":[70,113],"interpretable":[73],"ML":[74,117],"(IML)":[75],"(one":[77],"linear":[78],"one":[80],"nonlinear":[81],"model)":[82],"provided":[83,156],"us":[84],"with":[85,127],"better":[86,167],"feature":[91],"sets.":[92],"Following":[93],"study,":[95],"nine":[96],"binary":[97],"classification":[98],"compared,":[101],"Accuracy,":[104],"Recall,":[105],"Area":[107],"Under":[108],"Curve":[110],"analyzed.":[112],"results":[114],"showed":[115],"employed":[119],"combination":[121],"features":[124],"genomes":[126],"position":[132],"genes":[134],"patients":[136],"significantly":[137],"improves":[138],"prediction.":[140],"We":[141],"demonstrated":[142],"inclusion":[145],"preprocessed":[148],"patient":[149],"data":[150],"especially":[152],"through":[153],"information":[155],"IML":[158],"models,":[159],"clinicians":[162],"understand":[164],"make":[169],"informed":[170],"treatment":[171],"decisions.":[172]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}
