{"id":"https://openalex.org/W2530279937","doi":"https://doi.org/10.1007/s10278-016-9914-9","title":"High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks","display_name":"High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks","publication_year":2016,"publication_date":"2016-10-11","ids":{"openalex":"https://openalex.org/W2530279937","doi":"https://doi.org/10.1007/s10278-016-9914-9","mag":"2530279937","pmid":"https://pubmed.ncbi.nlm.nih.gov/27730417"},"language":"en","primary_location":{"id":"doi:10.1007/s10278-016-9914-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10278-016-9914-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10278-016-9914-9.pdf","source":{"id":"https://openalex.org/S62275304","display_name":"Journal of Digital Imaging","issn_l":"0897-1889","issn":["0897-1889","1618-727X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Digital Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10278-016-9914-9.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022388476","display_name":"Alvin Rajkomar","orcid":"https://orcid.org/0000-0001-5750-5016"},"institutions":[{"id":"https://openalex.org/I180670191","display_name":"University of California, San Francisco","ror":"https://ror.org/043mz5j54","country_code":"US","type":"education","lineage":["https://openalex.org/I180670191"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Alvin Rajkomar","raw_affiliation_strings":["Center for Digital Health Innovation, University of California, San Francisco, San Francisco, CA, USA. Alvin.rajkomar@ucsf.edu","Department of Medicine, Division of Hospital Medicine, University of California, San Francisco, 533 Parnassus Ave., Suite 127a, San Francisco, CA, 94143-0131, USA. Alvin.rajkomar@ucsf.edu","Department of Medicine, Division of Hospital Medicine, University of California, San Francisco, 533 Parnassus Ave., Suite 127a, San Francisco, CA, 94143-0131, USA"],"affiliations":[{"raw_affiliation_string":"Center for Digital Health Innovation, University of California, San Francisco, San Francisco, CA, USA. Alvin.rajkomar@ucsf.edu","institution_ids":[]},{"raw_affiliation_string":"Department of Medicine, Division of Hospital Medicine, University of California, San Francisco, 533 Parnassus Ave., Suite 127a, San Francisco, CA, 94143-0131, USA. Alvin.rajkomar@ucsf.edu","institution_ids":[]},{"raw_affiliation_string":"Department of Medicine, Division of Hospital Medicine, University of California, San Francisco, 533 Parnassus Ave., Suite 127a, San Francisco, CA, 94143-0131, USA","institution_ids":["https://openalex.org/I180670191"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108013173","display_name":"Sneha Lingam","orcid":"https://orcid.org/0000-0001-7821-7638"},"institutions":[{"id":"https://openalex.org/I4210110459","display_name":"City of Hope","ror":"https://ror.org/01z1vct10","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1301076528","https://openalex.org/I4210110459"]},{"id":"https://openalex.org/I180670191","display_name":"University of California, San Francisco","ror":"https://ror.org/043mz5j54","country_code":"US","type":"education","lineage":["https://openalex.org/I180670191"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sneha Lingam","raw_affiliation_strings":["Center for Digital Health Innovation, University of California, San Francisco, San Francisco, CA, USA"],"affiliations":[{"raw_affiliation_string":"Center for Digital Health Innovation, University of California, San Francisco, San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210110459","https://openalex.org/I180670191"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073494009","display_name":"Andrew Taylor","orcid":"https://orcid.org/0000-0002-4198-4232"},"institutions":[{"id":"https://openalex.org/I180670191","display_name":"University of California, San Francisco","ror":"https://ror.org/043mz5j54","country_code":"US","type":"education","lineage":["https://openalex.org/I180670191"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew G. Taylor","raw_affiliation_strings":["Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA","institution_ids":["https://openalex.org/I180670191"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109340915","display_name":"Michael Blum","orcid":"https://orcid.org/0009-0000-8989-9494"},"institutions":[{"id":"https://openalex.org/I4210110459","display_name":"City of Hope","ror":"https://ror.org/01z1vct10","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1301076528","https://openalex.org/I4210110459"]},{"id":"https://openalex.org/I180670191","display_name":"University of California, San Francisco","ror":"https://ror.org/043mz5j54","country_code":"US","type":"education","lineage":["https://openalex.org/I180670191"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Blum","raw_affiliation_strings":["Center for Digital Health Innovation, University of California, San Francisco, San Francisco, CA, USA"],"affiliations":[{"raw_affiliation_string":"Center for Digital Health Innovation, University of California, San Francisco, San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210110459","https://openalex.org/I180670191"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053343994","display_name":"John Mongan","orcid":"https://orcid.org/0000-0003-2765-7451"},"institutions":[{"id":"https://openalex.org/I180670191","display_name":"University of California, San Francisco","ror":"https://ror.org/043mz5j54","country_code":"US","type":"education","lineage":["https://openalex.org/I180670191"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John Mongan","raw_affiliation_strings":["Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA","institution_ids":["https://openalex.org/I180670191"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5022388476"],"corresponding_institution_ids":["https://openalex.org/I180670191"],"apc_list":{"value":3190,"currency":"EUR","value_usd":4190},"apc_paid":{"value":3190,"currency":"EUR","value_usd":4190},"fwci":15.4093,"has_fulltext":true,"cited_by_count":142,"citation_normalized_percentile":{"value":0.99421985,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"30","issue":"1","first_page":"95","last_page":"101"},"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":0.9957000017166138,"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":0.9957000017166138,"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/T10862","display_name":"AI in cancer detection","score":0.9951000213623047,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9922000169754028,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8290421962738037},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7030288577079773},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.6566681861877441},{"id":"https://openalex.org/keywords/radiography","display_name":"Radiography","score":0.63191819190979},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5958837270736694},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4574204981327057},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4403787851333618},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.3036803901195526},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.29920896887779236},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09483632445335388},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.06883281469345093}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8290421962738037},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7030288577079773},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.6566681861877441},{"id":"https://openalex.org/C36454342","wikidata":"https://www.wikidata.org/wiki/Q245341","display_name":"Radiography","level":2,"score":0.63191819190979},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5958837270736694},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4574204981327057},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4403787851333618},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.3036803901195526},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.29920896887779236},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09483632445335388},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.06883281469345093}],"mesh":[{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011859","descriptor_name":"Radiography","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false},{"descriptor_ui":"D011859","descriptor_name":"Radiography","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false},{"descriptor_ui":"D011859","descriptor_name":"Radiography","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false},{"descriptor_ui":"D011897","descriptor_name":"Random Allocation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011897","descriptor_name":"Random Allocation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011897","descriptor_name":"Random Allocation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012189","descriptor_name":"Retrospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012189","descriptor_name":"Retrospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012189","descriptor_name":"Retrospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":"Q000706","qualifier_name":"statistics & numerical data","is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.1007/s10278-016-9914-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10278-016-9914-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10278-016-9914-9.pdf","source":{"id":"https://openalex.org/S62275304","display_name":"Journal of Digital Imaging","issn_l":"0897-1889","issn":["0897-1889","1618-727X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Digital Imaging","raw_type":"journal-article"},{"id":"pmid:27730417","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/27730417","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of digital imaging","raw_type":null},{"id":"pmh:ark:/13030/qt5sd5688t","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},{"id":"pmh:oai:escholarship.org/ark:/13030/qt5sd5688t","is_oa":false,"landing_page_url":"https://escholarship.org/uc/item/5sd5688t","pdf_url":null,"source":{"id":"https://openalex.org/S4306400115","display_name":"eScholarship (California Digital Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2801248553","host_organization_name":"California Digital Library","host_organization_lineage":["https://openalex.org/I2801248553"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of digital imaging, vol 30, iss 1","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:5267603","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5267603","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Digit Imaging","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1007/s10278-016-9914-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10278-016-9914-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10278-016-9914-9.pdf","source":{"id":"https://openalex.org/S62275304","display_name":"Journal of Digital Imaging","issn_l":"0897-1889","issn":["0897-1889","1618-727X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Digital Imaging","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2530279937.pdf","grobid_xml":"https://content.openalex.org/works/W2530279937.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W948663339","https://openalex.org/W1589459581","https://openalex.org/W2057162280","https://openalex.org/W2058961400","https://openalex.org/W2077375822","https://openalex.org/W2084220915","https://openalex.org/W2097117768","https://openalex.org/W2112224175","https://openalex.org/W2117539524","https://openalex.org/W2136922672","https://openalex.org/W2137591261","https://openalex.org/W2149933564","https://openalex.org/W2152575748","https://openalex.org/W2152772232","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2274227799","https://openalex.org/W2307535535","https://openalex.org/W2323929895","https://openalex.org/W2334763311","https://openalex.org/W2338271170","https://openalex.org/W2394863728","https://openalex.org/W2919115771"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W2136583354","https://openalex.org/W2111238207","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"The":[0,53,122,183],"study":[1,160],"aimed":[2],"to":[3,20,78,130,148,165],"determine":[4],"if":[5],"computer":[6],"vision":[7],"techniques":[8],"rooted":[9],"in":[10,231],"deep":[11,92,215],"learning":[12],"can":[13],"use":[14],"a":[15,89,136,150,242],"small":[16],"set":[17,134,149,200,226],"of":[18,91,103,196,227,235],"radiographs":[19,35,180,228],"perform":[21],"clinically":[22],"relevant":[23],"image":[24,84],"classification":[25,185,234],"with":[26,100,124],"high":[27],"fidelity.":[28],"One":[29],"thousand":[30],"eight":[31],"hundred":[32],"eighty-five":[33],"chest":[34,236],"on":[36,96,170,178],"909":[37],"patients":[38],"obtained":[39],"between":[40],"January":[41],"2013":[42],"and":[43,51,63,69,73,118,135,176,201,223,240],"July":[44],"2015":[45],"at":[46,209],"our":[47,131,198],"institution":[48],"were":[49,56,76,112],"retrieved":[50],"anonymized.":[52],"source":[54],"images":[55,81,175,211],"manually":[57],"annotated":[58],"as":[59],"frontal":[60,154],"or":[61,155],"lateral":[62,156],"randomly":[64],"divided":[65],"into":[66],"training,":[67],"validation,":[68],"test":[70,133,199],"sets.":[71],"Training":[72],"validation":[74,126],"sets":[75],"augmented":[77,119,179,225],"over":[79],"150,000":[80],"using":[82,115,144,220],"standard":[83],"manipulations.":[85],"We":[86],"then":[87,113],"pre-trained":[88,169],"series":[90],"convolutional":[93,216],"networks":[94,111],"based":[95],"the":[97,104,116,145,202],"open-source":[98,105],"GoogLeNet":[99],"various":[101],"transformations":[102],"ImageNet":[106,174],"(non-radiology)":[107],"images.":[108,121,205],"These":[109],"trained":[110],"fine-tuned":[114,177],"original":[117],"radiology":[120],"model":[123],"highest":[125],"accuracy":[127],"was":[128,141,161,181,207],"applied":[129],"institutional":[132],"publicly":[137,203],"available":[138,204],"set.":[139],"Accuracy":[140],"assessed":[142],"by":[143],"Youden":[146],"Index":[147],"binary":[151,184],"cutoff":[152],"for":[153,246],"classification.":[157],"This":[158],"retrospective":[159],"IRB":[162],"approved":[163],"prior":[164],"initiation.":[166],"A":[167,214],"network":[168,218],"1.2":[171],"million":[172],"greyscale":[173],"chosen.":[182],"method":[186,245],"correctly":[187],"classified":[188],"100":[189],"%":[190,192],"(95":[191],"CI":[193],"99.73-100":[194],"%)":[195],"both":[197],"Classification":[206],"rapid,":[208],"38":[210],"per":[212],"second.":[213],"neural":[217],"created":[219],"non-radiological":[221],"images,":[222],"an":[224],"is":[229,241],"effective":[230],"highly":[232],"accurate":[233],"radiograph":[237],"view":[238],"type":[239],"feasible,":[243],"rapid":[244],"high-throughput":[247],"annotation.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":24},{"year":2020,"cited_by_count":18},{"year":2019,"cited_by_count":25},{"year":2018,"cited_by_count":17},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
