{"id":"https://openalex.org/W4320024317","doi":"https://doi.org/10.1109/bigdata55660.2022.10020356","title":"Radiopaths: Deep Multimodal Analysis on Chest Radiographs","display_name":"Radiopaths: Deep Multimodal Analysis on Chest Radiographs","publication_year":2022,"publication_date":"2022-12-17","ids":{"openalex":"https://openalex.org/W4320024317","doi":"https://doi.org/10.1109/bigdata55660.2022.10020356"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata55660.2022.10020356","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020356","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","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/A5090319595","display_name":"Mohammad Kohankhaki","orcid":null},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Mohammad Kohankhaki","raw_affiliation_strings":["RWTH Aachen University,Chair of Information Theory and Data Analytics,Aachen,Germany,D-52074"],"affiliations":[{"raw_affiliation_string":"RWTH Aachen University,Chair of Information Theory and Data Analytics,Aachen,Germany,D-52074","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025162594","display_name":"Ahmad Ayad","orcid":"https://orcid.org/0000-0002-9081-1274"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ahmad Ayad","raw_affiliation_strings":["RWTH Aachen University,Chair of Information Theory and Data Analytics,Aachen,Germany,D-52074"],"affiliations":[{"raw_affiliation_string":"RWTH Aachen University,Chair of Information Theory and Data Analytics,Aachen,Germany,D-52074","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028312507","display_name":"Mahdi Barhoush","orcid":"https://orcid.org/0000-0002-3787-0662"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mahdi Barhoush","raw_affiliation_strings":["RWTH Aachen University,Chair of Information Theory and Data Analytics,Aachen,Germany,D-52074"],"affiliations":[{"raw_affiliation_string":"RWTH Aachen University,Chair of Information Theory and Data Analytics,Aachen,Germany,D-52074","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071006649","display_name":"Bastian Leibe","orcid":"https://orcid.org/0000-0003-4225-0051"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bastian Leibe","raw_affiliation_strings":["RWTH Aachen University,Chair of Computer Vision,Aachen,Germany,D-52074"],"affiliations":[{"raw_affiliation_string":"RWTH Aachen University,Chair of Computer Vision,Aachen,Germany,D-52074","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072895220","display_name":"Anke Schmeink","orcid":"https://orcid.org/0000-0002-9929-2925"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Anke Schmeink","raw_affiliation_strings":["RWTH Aachen University,Chair of Information Theory and Data Analytics,Aachen,Germany,D-52074"],"affiliations":[{"raw_affiliation_string":"RWTH Aachen University,Chair of Information Theory and Data Analytics,Aachen,Germany,D-52074","institution_ids":["https://openalex.org/I887968799"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5090319595"],"corresponding_institution_ids":["https://openalex.org/I887968799"],"apc_list":null,"apc_paid":null,"fwci":0.6701,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.73192636,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"30","issue":null,"first_page":"3613","last_page":"3621"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9997000098228455,"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":0.9997000098228455,"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9690999984741211,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory 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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9114000201225281,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/chest-radiograph","display_name":"Chest radiograph","score":0.7568738460540771},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.653253972530365},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6025625467300415},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5942718982696533},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5399131774902344},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5160255432128906},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5033876299858093},{"id":"https://openalex.org/keywords/radiography","display_name":"Radiography","score":0.4840545058250427},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44177812337875366},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2965722978115082},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.2724888026714325}],"concepts":[{"id":"https://openalex.org/C2781137159","wikidata":"https://www.wikidata.org/wiki/Q1283318","display_name":"Chest radiograph","level":3,"score":0.7568738460540771},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.653253972530365},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6025625467300415},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5942718982696533},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5399131774902344},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5160255432128906},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5033876299858093},{"id":"https://openalex.org/C36454342","wikidata":"https://www.wikidata.org/wiki/Q245341","display_name":"Radiography","level":2,"score":0.4840545058250427},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44177812337875366},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2965722978115082},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.2724888026714325},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata55660.2022.10020356","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020356","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.6100000143051147}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W571200655","https://openalex.org/W1522301498","https://openalex.org/W2068258779","https://openalex.org/W2108598243","https://openalex.org/W2122653375","https://openalex.org/W2194775991","https://openalex.org/W2502805798","https://openalex.org/W2765793020","https://openalex.org/W2799108307","https://openalex.org/W2799534541","https://openalex.org/W2911489562","https://openalex.org/W2936762062","https://openalex.org/W2963351448","https://openalex.org/W2963446712","https://openalex.org/W2963466845","https://openalex.org/W2971686358","https://openalex.org/W2995225687","https://openalex.org/W3004417792","https://openalex.org/W3005030567","https://openalex.org/W3035356612","https://openalex.org/W3084346490","https://openalex.org/W3094595351","https://openalex.org/W3110181119","https://openalex.org/W3139379779","https://openalex.org/W3164968918","https://openalex.org/W3181252431","https://openalex.org/W3196927126","https://openalex.org/W4205512907","https://openalex.org/W4288076043","https://openalex.org/W4298395628","https://openalex.org/W4300485340","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6734194636","https://openalex.org/W6739901393","https://openalex.org/W6746693533","https://openalex.org/W6747620207","https://openalex.org/W6750490547","https://openalex.org/W6750774884","https://openalex.org/W6760958039","https://openalex.org/W6762718338","https://openalex.org/W6763367864","https://openalex.org/W6768085401","https://openalex.org/W6773574953","https://openalex.org/W6773835393","https://openalex.org/W6780226713"],"related_works":["https://openalex.org/W2185469136","https://openalex.org/W4241643913","https://openalex.org/W2011264131","https://openalex.org/W3022270872","https://openalex.org/W2025593094","https://openalex.org/W2241350146","https://openalex.org/W4255971525","https://openalex.org/W2127987400","https://openalex.org/W2512580829","https://openalex.org/W2140868683"],"abstract_inverted_index":{"Each":[0],"year,":[1],"pneumonia":[2,20,102],"causes":[3],"harm":[4],"to":[5,46,100,162],"millions":[6],"of":[7,37,56,137,149],"people":[8],"worldwide.":[9],"The":[10],"chest":[11,87,104],"radiograph":[12],"remains":[13],"the":[14,53,122,126,153],"most":[15],"important":[16],"tool":[17],"for":[18,71,86],"diagnosing":[19],"and":[21,42,74,89,165],"many":[22],"other":[23,109,118],"thoracic":[24],"diseases.":[25],"Many":[26],"deep-learning":[27],"approaches":[28,120],"have":[29],"been":[30],"advocated":[31],"in":[32,49,77,106,125],"recent":[33],"years,":[34],"taking":[35],"advantage":[36],"large":[38],"public":[39],"medical":[40,79],"datasets":[41],"powerful":[43],"computational":[44],"resources":[45],"support":[47],"radiologists":[48],"their":[50],"examinations.":[51],"However,":[52],"vast":[54],"amount":[55],"data":[57,76],"available":[58],"is":[59],"rarely":[60],"utilized.":[61],"In":[62],"this":[63],"work,":[64],"we":[65],"propose":[66],"two":[67],"novel":[68],"attention-based":[69,140],"mechanisms":[70,99],"fusing":[72],"multimodal":[73,91,141],"multi-view":[75,84,115,154],"a":[78,90],"context,":[80],"respectively.":[81],"A":[82],"unimodal":[83,114],"classifier":[85,92],"X-rays":[88],"are":[93],"developed,":[94],"inter":[95],"alia,":[96],"operating":[97],"these":[98],"classify":[101],"using":[103],"radiographs":[105],"combination":[107],"with":[108],"clinically":[110],"derived":[111],"modalities.":[112],"Our":[113,139],"model":[116],"outperforms":[117],"state-of-the-art":[119],"on":[121],"MIMIC-IV":[123],"dataset":[124],"AUROC":[127,135,147],"metric":[128],"by":[129,157],"at":[130],"least":[131],"9.2%,":[132],"achieving":[133],"an":[134,146],"score":[136,148],"81.5%.":[138],"model,":[142],"namely":[143],"Radiopaths,":[144],"achieved":[145],"87.3%,":[150],"further":[151],"increasing":[152],"model's":[155],"performance":[156],"5.8%,":[158],"while":[159],"acquiring":[160],"robustness":[161],"missing":[163],"modalities":[164],"scalability.":[166]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}