{"id":"https://openalex.org/W4225518663","doi":"https://doi.org/10.1117/12.2612984","title":"Selecting training samples for ovarian cancer classification via a semi-supervised clustering approach","display_name":"Selecting training samples for ovarian cancer classification via a semi-supervised clustering approach","publication_year":2022,"publication_date":"2022-04-04","ids":{"openalex":"https://openalex.org/W4225518663","doi":"https://doi.org/10.1117/12.2612984"},"language":"en","primary_location":{"id":"doi:10.1117/12.2612984","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2612984","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2022: Digital and Computational Pathology","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/A5031412020","display_name":"Jennifer Salguero","orcid":null},"institutions":[{"id":"https://openalex.org/I36243813","display_name":"Universidad Nacional de Colombia","ror":"https://ror.org/059yx9a68","country_code":"CO","type":"education","lineage":["https://openalex.org/I36243813"]}],"countries":["CO"],"is_corresponding":true,"raw_author_name":"Jennifer Salguero","raw_affiliation_strings":["Univ. Nacional de Colombia (Colombia)"],"affiliations":[{"raw_affiliation_string":"Univ. Nacional de Colombia (Colombia)","institution_ids":["https://openalex.org/I36243813"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036343196","display_name":"Prateek Prasanna","orcid":"https://orcid.org/0000-0002-3068-3573"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prateek Prasanna","raw_affiliation_strings":["Stony Brook Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Stony Brook Univ. (United States)","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043558349","display_name":"Germ\u00e1n Corredor","orcid":"https://orcid.org/0000-0003-3002-0937"},"institutions":[{"id":"https://openalex.org/I4210110978","display_name":"Louis Stokes Cleveland VA Medical Center","ror":"https://ror.org/01vrybr67","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1322918889","https://openalex.org/I2799886695","https://openalex.org/I4210110978","https://openalex.org/I4210127612"]},{"id":"https://openalex.org/I58956616","display_name":"Case Western Reserve University","ror":"https://ror.org/051fd9666","country_code":"US","type":"education","lineage":["https://openalex.org/I58956616"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Germ\u00e1n Corredor","raw_affiliation_strings":["Case Western Reserve Univ. (United States)","Louis Stokes VA Medical Ctr. (United States)"],"affiliations":[{"raw_affiliation_string":"Case Western Reserve Univ. (United States)","institution_ids":["https://openalex.org/I58956616"]},{"raw_affiliation_string":"Louis Stokes VA Medical Ctr. (United States)","institution_ids":["https://openalex.org/I4210110978"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072005501","display_name":"\u00c1ngel Cruz-Roa","orcid":"https://orcid.org/0000-0003-3389-8913"},"institutions":[{"id":"https://openalex.org/I3129686679","display_name":"University of the Llanos","ror":"https://ror.org/042335e16","country_code":"CO","type":"education","lineage":["https://openalex.org/I3129686679"]}],"countries":["CO"],"is_corresponding":false,"raw_author_name":"Angel Cruz-Roa","raw_affiliation_strings":["Univ. de los Llanos (Colombia)"],"affiliations":[{"raw_affiliation_string":"Univ. de los Llanos (Colombia)","institution_ids":["https://openalex.org/I3129686679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014278738","display_name":"David Becerra Tovar","orcid":null},"institutions":[{"id":"https://openalex.org/I36243813","display_name":"Universidad Nacional de Colombia","ror":"https://ror.org/059yx9a68","country_code":"CO","type":"education","lineage":["https://openalex.org/I36243813"]}],"countries":["CO"],"is_corresponding":false,"raw_author_name":"David Becerra Tovar","raw_affiliation_strings":["Univ. Nacional de Colombia (Colombia)"],"affiliations":[{"raw_affiliation_string":"Univ. Nacional de Colombia (Colombia)","institution_ids":["https://openalex.org/I36243813"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102790773","display_name":"Eduardo Romero","orcid":"https://orcid.org/0000-0003-2088-2509"},"institutions":[{"id":"https://openalex.org/I36243813","display_name":"Universidad Nacional de Colombia","ror":"https://ror.org/059yx9a68","country_code":"CO","type":"education","lineage":["https://openalex.org/I36243813"]}],"countries":["CO"],"is_corresponding":false,"raw_author_name":"Eduardo Romero Castro","raw_affiliation_strings":["Univ. Nacional de Colombia (Colombia)"],"affiliations":[{"raw_affiliation_string":"Univ. Nacional de Colombia (Colombia)","institution_ids":["https://openalex.org/I36243813"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5031412020"],"corresponding_institution_ids":["https://openalex.org/I36243813"],"apc_list":null,"apc_paid":null,"fwci":0.2776,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61157018,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"8","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9991000294685364,"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":0.9991000294685364,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9868999719619751,"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/computer-science","display_name":"Computer science","score":0.7759270071983337},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7019778490066528},{"id":"https://openalex.org/keywords/probabilistic-latent-semantic-analysis","display_name":"Probabilistic latent semantic analysis","score":0.6997108459472656},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6083427667617798},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5891426205635071},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5359981656074524},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4231623709201813},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.41835668683052063}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7759270071983337},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7019778490066528},{"id":"https://openalex.org/C112933361","wikidata":"https://www.wikidata.org/wiki/Q2845258","display_name":"Probabilistic latent semantic analysis","level":2,"score":0.6997108459472656},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6083427667617798},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5891426205635071},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5359981656074524},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4231623709201813},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.41835668683052063},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2612984","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2612984","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2022: Digital and Computational Pathology","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2617669016","https://openalex.org/W2923812673","https://openalex.org/W2963989179","https://openalex.org/W3164897936","https://openalex.org/W4233135949"],"related_works":["https://openalex.org/W1657880117","https://openalex.org/W2595172197","https://openalex.org/W2127970246","https://openalex.org/W2084856301","https://openalex.org/W1001352512","https://openalex.org/W4382618745","https://openalex.org/W4389358162","https://openalex.org/W2885125400","https://openalex.org/W2033524022","https://openalex.org/W1989889224"],"abstract_inverted_index":{"Machine":[0],"learning":[1],"techniques":[2],"have":[3],"shown":[4],"great":[5],"promise":[6],"in":[7,187,204,210],"digital":[8],"pathology.":[9],"However,":[10],"a":[11,67,75,82,92,98,122,160,164,188,200],"major":[12],"bottleneck":[13],"is":[14,142],"the":[15,49,106,145,154,171,175,205,211],"difficulty":[16],"of":[17,21,42,51,95,117,167,177,190,202,213],"annotating":[18],"necessary":[19],"amount":[20],"tissue":[22],"to":[23,73,221],"deal":[24],"with":[25,97,135,150,163,195],"several":[26],"variability":[27],"factors,":[28],"namely":[29],"chemical":[30],"fixation,":[31],"sample":[32,71],"slicing,":[33],"or":[34],"staining.":[35],"Usually,":[36],"models":[37],"are":[38,179],"trained":[39,100,162],"using":[40,144],"sets":[41],"annotated":[43,168],"small":[44],"image":[45],"patches,":[46],"but":[47],"then,":[48],"number":[50,176,212],"required":[52],"patches":[53,96,104,120,148,151,169,191],"may":[54],"increase":[55],"exponentially":[56],"and":[57,102,111,132,174,208],"yet":[58],"they":[59],"must":[60],"represent":[61],"such":[62],"variability.":[63],"This":[64,157],"paper":[65],"presents":[66],"method":[68,88],"for":[69,77],"automatic":[70],"selection":[72,116],"train":[74],"classifier":[76,101],"ovarian":[78],"cancer":[79,107],"by":[80,90,121],"integrating":[81],"novel":[83],"soft":[84],"clustering":[85],"strategy.":[86],"The":[87,183],"starts":[89],"classifying":[91],"large":[93],"set":[94,166,189],"previously":[99],"divide":[103],"from":[105,130,153,192,219],"class":[108],"as":[109],"highly":[110,146],"moderately":[112,118],"confident.":[113],"An":[114],"unsupervised":[115],"confident":[119,147],"Probabilistic":[123],"Latent":[124],"Semantic":[125],"Analysis":[126],"(PLSA),":[127],"picks":[128],"samples":[129,178],"<i>relevant":[131],"meaningful</i>":[133],"groups":[134],"maximum":[136],"within-group":[137],"variance.":[138],"A":[139],"new":[140],"model":[141,161],"re-trained":[143],"together":[149],"obtained":[152],"associated":[155],"PLSA.":[156],"strategy":[158,184],"outperforms":[159],"larger":[165],"while":[170,215],"training":[172,206],"times":[173],"much":[180],"more":[181],"smaller.":[182],"was":[185],"evaluated":[186],"18":[193],"patients":[194],"Serous":[196],"Ovarian":[197],"Cancer,":[198],"obtaining":[199],"reduction":[201],"54.62%":[203],"time":[207],"73.66%":[209],"samples,":[214],"recall":[216],"rate":[217],"improved":[218],"0.69":[220],"0.73.":[222]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-16T15:07:20.185449","created_date":"2025-10-10T00:00:00"}