{"id":"https://openalex.org/W2922401630","doi":"https://doi.org/10.1117/12.2512886","title":"Combining deep learning methods and human knowledge to identify abnormalities in computed tomography (CT) reports","display_name":"Combining deep learning methods and human knowledge to identify abnormalities in computed tomography (CT) reports","publication_year":2019,"publication_date":"2019-03-13","ids":{"openalex":"https://openalex.org/W2922401630","doi":"https://doi.org/10.1117/12.2512886","mag":"2922401630"},"language":"en","primary_location":{"id":"doi:10.1117/12.2512886","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2512886","pdf_url":null,"source":{"id":"https://openalex.org/S4306519510","display_name":"Medical Imaging 2019: 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 2019: Computer-Aided Diagnosis","raw_type":"proceedings-article"},"type":"conference-paper","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/A5053304521","display_name":"Matias Giuliano Gutierrez Benitez","orcid":null},"institutions":[{"id":"https://openalex.org/I4210088741","display_name":"Clinical Research Institute","ror":"https://ror.org/009ywjj88","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210088741"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matias  . Benitez","raw_affiliation_strings":["Duke Clinical Research Institute (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke Clinical Research Institute (United States)","institution_ids":["https://openalex.org/I4210088741"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023969960","display_name":"Vignesh Selvakumaran","orcid":"https://orcid.org/0000-0001-5065-8132"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vignesh Selvakumaran","raw_affiliation_strings":["Duke Univ. School of Medicine (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke Univ. School of Medicine (United States)","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108724648","display_name":"James Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Tian","raw_affiliation_strings":["Duke Univ. School of Medicine (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke Univ. School of Medicine (United States)","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003197350","display_name":"Matthew Phelan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210088741","display_name":"Clinical Research Institute","ror":"https://ror.org/009ywjj88","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210088741"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew Phelan","raw_affiliation_strings":["Duke Clinical Research Institute (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke Clinical Research Institute (United States)","institution_ids":["https://openalex.org/I4210088741"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040192736","display_name":"Joseph Y. Lo","orcid":"https://orcid.org/0000-0002-9540-5072"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joseph Y. Lo","raw_affiliation_strings":["Duke Univ. (United States)","Duke Univ. School of Medicine (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke Univ. (United States)","institution_ids":["https://openalex.org/I170897317"]},{"raw_affiliation_string":"Duke Univ. School of Medicine (United States)","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091834429","display_name":"Geoffrey D. Rubin","orcid":"https://orcid.org/0000-0002-3820-2500"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Geoffrey Rubin","raw_affiliation_strings":["Duke Univ. School of Medicine (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke Univ. School of Medicine (United States)","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056639842","display_name":"Ricardo Henao","orcid":"https://orcid.org/0000-0003-4980-845X"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]},{"id":"https://openalex.org/I4210088741","display_name":"Clinical Research Institute","ror":"https://ror.org/009ywjj88","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210088741"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ricardo Henao","raw_affiliation_strings":["Duke Clinical Research Institute (United States)","Duke Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke Clinical Research Institute (United States)","institution_ids":["https://openalex.org/I4210088741"]},{"raw_affiliation_string":"Duke Univ. (United States)","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mark Kelly","orcid":null},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mark Kelly","raw_affiliation_strings":["Duke Univ. School of Medicine (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke Univ. School of Medicine (United States)","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001300575","display_name":"Maciej A. Mazurowski","orcid":"https://orcid.org/0000-0003-4202-8602"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maciej A. Mazurowski","raw_affiliation_strings":["Duke Univ. (United States)","Duke Univ. School of Medicine (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke Univ. (United States)","institution_ids":["https://openalex.org/I170897317"]},{"raw_affiliation_string":"Duke Univ. School of Medicine (United States)","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2977,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.52434173,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"30","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9976000189781189,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9976000189781189,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9873999953269958,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9854000210762024,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6993224024772644},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6799325346946716},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.647563636302948},{"id":"https://openalex.org/keywords/computed-tomography","display_name":"Computed tomography","score":0.6246044039726257},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4925309121608734},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47902244329452515},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.45153361558914185},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4344896674156189},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.20680376887321472},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.19313102960586548}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6993224024772644},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6799325346946716},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.647563636302948},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.6246044039726257},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4925309121608734},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47902244329452515},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.45153361558914185},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4344896674156189},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.20680376887321472},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.19313102960586548},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2512886","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2512886","pdf_url":null,"source":{"id":"https://openalex.org/S4306519510","display_name":"Medical Imaging 2019: 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 2019: Computer-Aided Diagnosis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5899999737739563,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W96276655","https://openalex.org/W2107131609","https://openalex.org/W2115305054","https://openalex.org/W2153081307","https://openalex.org/W2345010043","https://openalex.org/W2963912736","https://openalex.org/W4294170691","https://openalex.org/W6682691769","https://openalex.org/W6750851401"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4380075502","https://openalex.org/W2027108423","https://openalex.org/W1855666948","https://openalex.org/W2758561209","https://openalex.org/W1548095260","https://openalex.org/W2781711915","https://openalex.org/W2112817590","https://openalex.org/W1555291398"],"abstract_inverted_index":{"Many":[0],"researchers":[1],"in":[2,36,52,140,173,202],"the":[3,10,158,162,187,195,215,218,224,231,241],"field":[4],"of":[5,12,28,50,128,197,228,247,254],"machine":[6,22,131,268],"learning":[7,23,124,132,269],"have":[8],"addressed":[9],"problem":[11],"detecting":[13],"anomalies":[14,33,76],"within":[15,77],"Computed":[16],"Tomography":[17],"(CT)":[18],"scans.":[19,97],"Training":[20],"these":[21,58],"algorithms":[24],"requires":[25,45],"a":[26,41,72,87,130,178,209,252],"dataset":[27],"CT":[29,68,96,104,136,256],"scans":[30,69,257],"with":[31,164,208,261],"identified":[32],"(labels),":[34],"usually,":[35],"specific":[37,117],"organs.":[38],"This":[39,98,169,249],"represents":[40],"problem,":[42],"since":[43],"it":[44,146],"experts":[46,156],"to":[47,54,62,89,114,134,189,240],"review":[48,157],"thousands":[49],"images":[51],"order":[53],"create":[55,90],"labels":[56,91],"for":[57,92,110,200],"data.":[59],"We":[60,119,193],"aim":[61,113],"decrease":[63],"human":[64,264],"burden":[65],"at":[66],"labeling":[67],"by":[70,138,147,176,186,266],"developing":[71],"model":[73,133,163,188,210,219,242],"that":[74,80,126,160,251],"identifies":[75],"plain-text-based":[78],"reports":[79,105,137,150,239],"then":[81,144],"could":[82],"be":[83,259],"further":[84],"used":[85,185],"as":[86],"method":[88,199],"models":[93],"based":[94],"on":[95,212,230],"study":[99],"contains":[100],"more":[101],"than":[102],"4800":[103],"from":[106,243],"Duke":[107],"Health":[108],"System,":[109],"which":[111],"we":[112],"identify":[115],"organ":[116],"abnormalities.":[118],"propose":[120],"an":[121,221,244],"iterative":[122],"active":[123],"approach":[125],"consists":[127],"building":[129],"classify":[135],"abnormalities":[139,201],"different":[141],"organs":[142],"and":[143,204,271],"improving":[145],"actively":[148,237],"adding":[149,235],"sequentially.":[151],"At":[152],"each":[153],"iteration,":[154],"clinical":[155,272],"report":[159],"provides":[161],"highest":[165],"expected":[166],"information":[167],"gain.":[168],"process":[170],"is":[171,184],"done":[172],"real":[174],"time":[175],"using":[177],"web":[179],"interface.":[180],"Then,":[181],"this":[182],"datum":[183],"improve":[190],"its":[191],"performance.":[192],"evaluated":[194],"performance":[196],"our":[198],"kidneys":[203],"lungs.":[205],"When":[206],"starting":[207],"trained":[211],"99":[213],"reports,":[214],"results":[216],"show":[217],"achieves":[220],"Area":[222],"Under":[223],"Curve":[225],"(AUC)":[226],"score":[227],"0.93":[229],"test":[232],"set":[233,253],"after":[234],"130":[236],"labeled":[238,255],"unlabeled":[245],"pool":[246],"4,000.":[248],"suggests":[250],"can":[258],"obtained":[260],"significantly":[262],"reduced":[263],"work":[265],"combining":[267],"techniques":[270],"experts'":[273],"knowledge.":[274]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}