{"id":"https://openalex.org/W2776565386","doi":null,"title":"MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs","display_name":"MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs","publication_year":2017,"publication_date":"2017-12-11","ids":{"openalex":"https://openalex.org/W2776565386","mag":"2776565386"},"language":"en","primary_location":{"id":"mag:2776565386","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1712.06957","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"volume":null,"type":"preprint","indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://export.arxiv.org/pdf/1712.06957","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001094226","display_name":"Pranav Rajpurkar","orcid":"https://orcid.org/0000-0002-8030-3727","observed_orcids":["https://orcid.org/0000-0002-8030-3727"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pranav Rajpurkar","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-8030-3727","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039154483","display_name":"Jeremy Irvin","orcid":"https://orcid.org/0000-0002-0395-4403","observed_orcids":["https://orcid.org/0000-0002-0395-4403"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeremy Irvin","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-0395-4403","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074585380","display_name":"Aarti Bagul","orcid":"https://orcid.org/0009-0007-2643-5941","observed_orcids":["https://orcid.org/0009-0007-2643-5941"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aarti Bagul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001213758","display_name":"Daisy Yi Ding","orcid":"https://orcid.org/0000-0003-2914-9557","observed_orcids":["https://orcid.org/0000-0003-2914-9557"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daisy Yi Ding","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-2914-9557","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112300384","display_name":"Tony Duan","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tony Duan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021952938","display_name":"Hershel Mehta","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hershel Mehta","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084812990","display_name":"Brandon Yang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brandon Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066266556","display_name":"Kaylie Zhu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kaylie Zhu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052792042","display_name":"Dillon Laird","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dillon Laird","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037330636","display_name":"Robyn L. Ball","orcid":"https://orcid.org/0000-0002-7335-3339","observed_orcids":["https://orcid.org/0000-0002-7335-3339"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Robyn L. Ball","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-7335-3339","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087710258","display_name":"Curtis P. Langlotz","orcid":"https://orcid.org/0000-0002-8972-8051","observed_orcids":["https://orcid.org/0000-0002-8972-8051"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Curtis P. Langlotz","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-8972-8051","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013976422","display_name":"Katie S. Shpanskaya","orcid":"https://orcid.org/0000-0003-2741-4046","observed_orcids":["https://orcid.org/0000-0003-2741-4046","https://orcid.org/0000-0002-2180-2059"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Katie Shpanskaya","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-2741-4046","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038969629","display_name":"Matthew P. Lungren","orcid":"https://orcid.org/0000-0002-8591-5861","observed_orcids":["https://orcid.org/0000-0002-8591-5861","https://orcid.org/0000-0002-8457-9034"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Matthew P. Lungren","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-8591-5861","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5102617494","display_name":"Andrew Y. Ng","orcid":"https://orcid.org/0000-0001-5547-3196","observed_orcids":["https://orcid.org/0000-0001-5547-3196"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Andrew Y. Ng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":73,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9096999764442444,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9096999764442444,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.051100000739097595,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/T11894","display_name":"Radiology practices and education","score":0.008799999952316284,"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/musculoskeletal-radiographs","display_name":"musculoskeletal radiographs","score":0.9860000014305115},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"anomaly detection","score":0.8830000162124634},{"id":"https://openalex.org/keywords/dense-convolutional-neural-network","display_name":"dense convolutional neural network","score":0.6520000100135803},{"id":"https://openalex.org/keywords/cohen-s-kappa","display_name":"Cohen's kappa","score":0.5590000152587891}],"concepts":[{"id":"https://openalex.org/C36454342","wikidata":"https://www.wikidata.org/wiki/Q245341","display_name":"Radiography","level":2,"score":0.5138280987739563},{"id":"https://openalex.org/C2778724333","wikidata":"https://www.wikidata.org/wiki/Q14401","display_name":"Kappa","level":2,"score":0.48565638065338135},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47523927688598633},{"id":"https://openalex.org/C50965678","wikidata":"https://www.wikidata.org/wiki/Q2724302","display_name":"Abnormality","level":2,"score":0.46542733907699585},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4563567638397217},{"id":"https://openalex.org/C2780214079","wikidata":"https://www.wikidata.org/wiki/Q228537","display_name":"Forearm","level":2,"score":0.45457810163497925},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.4504287838935852},{"id":"https://openalex.org/C163864269","wikidata":"https://www.wikidata.org/wiki/Q1107106","display_name":"Cohen's kappa","level":2,"score":0.4443865120410919},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4255084991455078},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.42050036787986755},{"id":"https://openalex.org/C40993552","wikidata":"https://www.wikidata.org/wiki/Q514654","display_name":"Gold standard (test)","level":2,"score":0.419174462556839},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3953559994697571},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19312283396720886},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.15297147631645203},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10931417346000671},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2776565386","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1712.06957","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"mag:2776565386","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1712.06957","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8199999928474426}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W177004468","https://openalex.org/W1522301498","https://openalex.org/W1922655562","https://openalex.org/W1988032969","https://openalex.org/W1992579055","https://openalex.org/W2018875682","https://openalex.org/W2042716610","https://openalex.org/W2052186216","https://openalex.org/W2061800045","https://openalex.org/W2093267329","https://openalex.org/W2108598243","https://openalex.org/W2142514727","https://openalex.org/W2152772232","https://openalex.org/W2154461664","https://openalex.org/W2295107390","https://openalex.org/W2427527485","https://openalex.org/W2557738935","https://openalex.org/W2581082771","https://openalex.org/W2611650229","https://openalex.org/W2731010577","https://openalex.org/W2766666652","https://openalex.org/W2770241596","https://openalex.org/W2772723798","https://openalex.org/W2963446712","https://openalex.org/W4294214983"],"related_works":["https://openalex.org/W2803124023","https://openalex.org/W3164688220","https://openalex.org/W3034104969","https://openalex.org/W3093633899","https://openalex.org/W3033383454","https://openalex.org/W3159215820","https://openalex.org/W4390120032","https://openalex.org/W3112684686","https://openalex.org/W3034144353","https://openalex.org/W7221067248"],"abstract_inverted_index":{"We":[0,74,111],"introduce":[1],"MURA,":[2],"a":[3,33,106,168],"large":[4],"dataset":[5,181],"of":[6,54,70,89,93,105,109,121],"musculoskeletal":[7,72],"radiographs":[8],"containing":[9],"40,895":[10],"images":[11],"from":[12,61],"14,982":[13],"studies,":[14,162],"where":[15],"each":[16,94],"study":[17],"is":[18,125,146,167],"manually":[19],"labeled":[20],"by":[21],"radiologists":[22,64,79],"as":[23,101],"either":[24],"normal":[25],"or":[26],"abnormal.":[27],"On":[28],"this":[29,185],"dataset,":[30],"we":[31,57,177],"train":[32],"169-layer":[34],"densely":[35],"connected":[36],"convolutional":[37],"network":[38],"to":[39,50,119],"detect":[40],"and":[41,49,78,92,138,160],"localize":[42],"abnormalities.":[43],"To":[44,174],"evaluate":[45],"our":[46,76,90,114,180],"model":[47,77,91,115,144],"robustly":[48],"get":[51],"an":[52],"estimate":[53],"radiologist":[55,95,130,150],"performance,":[56],"collect":[58],"additional":[59],"labels":[60],"board-certified":[62],"Stanford":[63],"on":[65,80,135,140,155],"the":[66,81,87,97,102,128,165],"test":[67],"set,":[68],"consisting":[69],"209":[71],"studies.":[73,142],"compared":[75],"Cohen's":[82],"kappa":[83],"statistic,":[84],"which":[85],"expresses":[86],"agreement":[88],"with":[96],"gold":[98],"standard,":[99],"defined":[100],"majority":[103],"vote":[104],"disjoint":[107],"group":[108],"radiologists.":[110,122],"find":[112],"that":[113,120,164],"achieves":[116],"performance":[117,124,131,145,151],"comparable":[118],"Model":[123],"higher":[126],"than":[127,148],"best":[129,149],"in":[132,152],"detecting":[133,153],"abnormalities":[134,154],"finger":[136],"studies":[137],"equivalent":[139],"wrist":[141],"However,":[143],"lower":[147],"elbow,":[156],"forearm,":[157],"hand,":[158],"humerus,":[159],"shoulder":[161],"indicating":[163],"task":[166],"good":[169],"challenge":[170],"for":[171],"future":[172],"research.":[173],"encourage":[175],"advances,":[176],"have":[178],"made":[179],"freely":[182],"available":[183],"at":[184],"https":[186],"URL":[187]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":15},{"year":2018,"cited_by_count":5}],"updated_date":"2026-10-17T09:40:24.721904","created_date":"2018-01-05T00:00:00"}