{"id":"https://openalex.org/W3011854996","doi":"https://doi.org/10.1117/12.2548144","title":"Case-based repeatability of machine learning classification performance on breast MRI","display_name":"Case-based repeatability of machine learning classification performance on breast MRI","publication_year":2020,"publication_date":"2020-03-16","ids":{"openalex":"https://openalex.org/W3011854996","doi":"https://doi.org/10.1117/12.2548144","mag":"3011854996"},"language":"en","primary_location":{"id":"doi:10.1117/12.2548144","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2548144","pdf_url":null,"source":{"id":"https://openalex.org/S4306519512","display_name":"Medical Imaging 2020: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Computer-Aided Diagnosis","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/A5012915209","display_name":"Michael Vieceli","orcid":null},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]},{"id":"https://openalex.org/I73236664","display_name":"Wheaton College - Illinois","ror":"https://ror.org/0581k0452","country_code":"US","type":"education","lineage":["https://openalex.org/I73236664"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Michael Vieceli","raw_affiliation_strings":["The Univ. of Chicago (United States)","Wheaton College (United States)"],"affiliations":[{"raw_affiliation_string":"The Univ. of Chicago (United States)","institution_ids":["https://openalex.org/I40347166"]},{"raw_affiliation_string":"Wheaton College (United States)","institution_ids":["https://openalex.org/I73236664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027681743","display_name":"Amy Van Dusen","orcid":null},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]},{"id":"https://openalex.org/I73236664","display_name":"Wheaton College - Illinois","ror":"https://ror.org/0581k0452","country_code":"US","type":"education","lineage":["https://openalex.org/I73236664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amy Van Dusen","raw_affiliation_strings":["The Univ. of Chicago (United States)","Wheaton College (United States)"],"affiliations":[{"raw_affiliation_string":"The Univ. of Chicago (United States)","institution_ids":["https://openalex.org/I40347166"]},{"raw_affiliation_string":"Wheaton College (United States)","institution_ids":["https://openalex.org/I73236664"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024321936","display_name":"Karen Drukker","orcid":"https://orcid.org/0000-0001-6544-3476"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karen Drukker","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025334715","display_name":"Hiroyuki Ab\u00e9","orcid":"https://orcid.org/0000-0002-3568-1462"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hiroyuki Abe","raw_affiliation_strings":["The Univ. of Chicago (United States)"],"affiliations":[{"raw_affiliation_string":"The Univ. of Chicago (United States)","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049042648","display_name":"Maryellen L. Giger","orcid":"https://orcid.org/0000-0001-5482-9728"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maryellen L. Giger","raw_affiliation_strings":["The Univ. of Chicago (United States)"],"affiliations":[{"raw_affiliation_string":"The Univ. of Chicago (United States)","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032409695","display_name":"Heather M. Whitney","orcid":"https://orcid.org/0000-0002-7258-1102"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]},{"id":"https://openalex.org/I73236664","display_name":"Wheaton College - Illinois","ror":"https://ror.org/0581k0452","country_code":"US","type":"education","lineage":["https://openalex.org/I73236664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Heather M. Whitney","raw_affiliation_strings":["The Univ. of Chicago (United States)","Wheaton College (United States)"],"affiliations":[{"raw_affiliation_string":"The Univ. of Chicago (United States)","institution_ids":["https://openalex.org/I40347166"]},{"raw_affiliation_string":"Wheaton College (United States)","institution_ids":["https://openalex.org/I73236664"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5012915209"],"corresponding_institution_ids":["https://openalex.org/I40347166","https://openalex.org/I73236664"],"apc_list":null,"apc_paid":null,"fwci":0.5507,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.6913325,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"70","last_page":"70"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":1.0,"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/T11885","display_name":"MRI in cancer diagnosis","score":0.9988999962806702,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9894999861717224,"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/repeatability","display_name":"Repeatability","score":0.9145850539207458},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.7435591816902161},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.5874046683311462},{"id":"https://openalex.org/keywords/ductal-carcinoma","display_name":"Ductal carcinoma","score":0.5848464369773865},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5064691305160522},{"id":"https://openalex.org/keywords/fibroadenoma","display_name":"Fibroadenoma","score":0.45643579959869385},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44387397170066833},{"id":"https://openalex.org/keywords/bi-rads","display_name":"BI-RADS","score":0.43900173902511597},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42215216159820557},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.3839196264743805},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.362165629863739},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.3536815047264099},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32302817702293396},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.31355583667755127},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30563420057296753},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.23176974058151245},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.1736546754837036},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16636142134666443}],"concepts":[{"id":"https://openalex.org/C154020017","wikidata":"https://www.wikidata.org/wiki/Q520171","display_name":"Repeatability","level":2,"score":0.9145850539207458},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.7435591816902161},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.5874046683311462},{"id":"https://openalex.org/C2780862961","wikidata":"https://www.wikidata.org/wiki/Q5311598","display_name":"Ductal carcinoma","level":4,"score":0.5848464369773865},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5064691305160522},{"id":"https://openalex.org/C2776524808","wikidata":"https://www.wikidata.org/wiki/Q1410808","display_name":"Fibroadenoma","level":4,"score":0.45643579959869385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44387397170066833},{"id":"https://openalex.org/C2779098232","wikidata":"https://www.wikidata.org/wiki/Q903975","display_name":"BI-RADS","level":5,"score":0.43900173902511597},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42215216159820557},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.3839196264743805},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.362165629863739},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.3536815047264099},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32302817702293396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.31355583667755127},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30563420057296753},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.23176974058151245},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.1736546754837036},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16636142134666443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2548144","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2548144","pdf_url":null,"source":{"id":"https://openalex.org/S4306519512","display_name":"Medical Imaging 2020: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Computer-Aided Diagnosis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.699999988079071,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2368942523","https://openalex.org/W2119418116","https://openalex.org/W2054704224","https://openalex.org/W2060374165","https://openalex.org/W3167588365","https://openalex.org/W3208212708","https://openalex.org/W4250996542","https://openalex.org/W4282053800","https://openalex.org/W2384277228","https://openalex.org/W316473529"],"abstract_inverted_index":{"Computer-aided":[0],"diagnosis":[1,8],"and":[2,9,26,65,106,133,141,193,204,211,233,263],"radiomics":[3],"have":[4],"shown":[5],"potential":[6,206],"in":[7,81,94,271,281,288],"prognosis":[10],"of":[11,16,23,32,41,79,110,158,173,178,197],"breast":[12,33,43],"cancer.":[13],"The":[14,55],"purpose":[15],"this":[17],"study":[18],"was":[19,161],"to":[20,29],"investigate":[21],"repeatability":[22,167,186,239,287],"classifier":[24,159],"output":[25,160],"its":[27],"relationship":[28,207],"classification":[30,72,154,209,214,278],"performance":[31,155,210,215,279],"lesions":[34,44,56],"imaged":[35],"with":[36,76,100],"dynamic":[37],"contrast-enhanced":[38],"MRI.":[39],"Images":[40],"1,169":[42],"(267":[45],"benign,":[46],"902":[47],"cancers)":[48],"were":[49,57,69,74,131,226,256],"retrospectively":[50],"collected":[51],"under":[52,146],"HIPAA/IRB":[53],"compliance.":[54],"segmented":[58],"automatically":[59],"using":[60],"a":[61],"fuzzy":[62],"c-means":[63],"method":[64],"thirty-eight":[66],"radiomic":[67],"features":[68],"extracted.":[70],"Three":[71],"tasks":[73,225,275],"investigated,":[75],"different":[77],"proportions":[78],"cases":[80],"each":[82,125,183],"class:":[83],"(i)":[84],"benign":[85],"(23%)":[86],"vs.":[87,98,119],"malignant":[88],"(77%),":[89],"(ii)":[90],"\u201cpure\u201d":[91],"ductal":[92,102],"carcinoma":[93,103],"situ":[95],"(DCIS)":[96],"(25%)":[97],"DCIS":[99],"invasive":[101,108],"(IDC)":[104],"(75%),":[105],"(iii)":[107],"cancers":[109],"molecular":[111,121],"subtype":[112],"luminal":[113,116],"A":[114],"or":[115],"B":[117],"(66%)":[118],"other":[120],"subtypes":[122],"(34%).":[123],"For":[124],"task,":[126],"support":[127],"vector":[128],"machine":[129],"classifiers":[130,270],"trained":[132],"tested":[134],"within":[135,187,241],"0.632+":[136,143],"bootstrap":[137],"analyses":[138],"(1000":[139],"iterations)":[140],"the":[142,147,153,174,188,198,223,242,244,253,269,272],"bias-corrected":[144],"area":[145],"ROC":[148],"curve":[149],"(AUC)":[150],"served":[151],"as":[152],"metric.":[156],"Repeatability":[157],"evaluated":[162],"at":[163],"three":[164,224,283],"levels:":[165],"a)":[166],"by":[168],"case":[169],"(performance":[170,190],"metric:":[171,191],"width":[172],"95%":[175,194,200],"confidence":[176,195,201,220,246,250],"interval":[177,196,202,247],"classifier-estimated":[179],"posterior":[180,254,289],"probabilities":[181,255],"for":[182,222,252],"case),":[184],"b)":[185],"dataset":[189],"median":[192,217,245],"by-case":[199],"widths),":[203],"c)":[205],"between":[208],"repeatability.":[212],"In":[213,238,267],"assessment,":[216],"AUCs":[218],"[95%":[219,249],"interval]":[221,251],"0.85":[227],"[0.83,":[228],"0.87],":[229,232],"0.84":[230],"[0.80,":[231],"0.65":[234],"[0.60,":[235],"0.69],":[236],"respectively.":[237],"assessment":[240],"dataset,":[243],"widths":[248],"0.25":[257],"[0.08,":[258],"0.72],":[259],"0.34":[260],"[0.14,":[261,265],"0.84],":[262],"0.23":[264],"0.68].":[266],"conclusion,":[268],"first":[273],"two":[274],"demonstrated":[276],"strong":[277],"while":[280],"all":[282],"they":[284],"showed":[285],"similar":[286],"probabilities.":[290]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}