{"id":"https://openalex.org/W3081612852","doi":"https://doi.org/10.1109/embc44109.2020.9176517","title":"Multi-View Ensemble Convolutional Neural Network to Improve Classification of Pneumonia in Low Contrast Chest X-Ray Images","display_name":"Multi-View Ensemble Convolutional Neural Network to Improve Classification of Pneumonia in Low Contrast Chest X-Ray Images","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3081612852","doi":"https://doi.org/10.1109/embc44109.2020.9176517","mag":"3081612852","pmid":"https://pubmed.ncbi.nlm.nih.gov/33018211"},"language":"en","primary_location":{"id":"doi:10.1109/embc44109.2020.9176517","is_oa":true,"landing_page_url":"https://doi.org/10.1109/embc44109.2020.9176517","pdf_url":"https://ieeexplore.ieee.org/ielx7/9167168/9175149/09176517.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 42nd Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/9167168/9175149/09176517.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056119195","display_name":"Jos\u00e9 Raniery Ferreira","orcid":"https://orcid.org/0000-0002-8202-588X"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Jose Raniery Ferreira","raw_affiliation_strings":["Heart Institute, Clinics Hospital, University of Sao Paulo Medical School, S\u00e3o Paulo, SP, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heart Institute, Clinics Hospital, University of Sao Paulo Medical School, S\u00e3o Paulo, SP, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101646759","display_name":"Diego Armando Cardona C\u00e1rdenas","orcid":"https://orcid.org/0000-0002-8846-5202"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Diego Armando Cardona Cardenas","raw_affiliation_strings":["Heart Institute, Clinics Hospital, University of Sao Paulo Medical School, S\u00e3o Paulo, SP, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heart Institute, Clinics Hospital, University of Sao Paulo Medical School, S\u00e3o Paulo, SP, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103272705","display_name":"Ramon A. Moreno","orcid":"https://orcid.org/0000-0002-0548-9365"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Ramon Alfredo Moreno","raw_affiliation_strings":["Heart Institute, Clinics Hospital, University of Sao Paulo Medical School, S\u00e3o Paulo, SP, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heart Institute, Clinics Hospital, University of Sao Paulo Medical School, S\u00e3o Paulo, SP, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058527360","display_name":"Marina de F\u00e1tima de S\u00e1 Rebelo","orcid":null},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Marina de Fatima de Sa Rebelo","raw_affiliation_strings":["Heart Institute, Clinics Hospital, University of Sao Paulo Medical School, S\u00e3o Paulo, SP, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heart Institute, Clinics Hospital, University of Sao Paulo Medical School, S\u00e3o Paulo, SP, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088604083","display_name":"Jos\u00e9 Eduardo Krieger","orcid":"https://orcid.org/0000-0001-5464-1792"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Jose Eduardo Krieger","raw_affiliation_strings":["Heart Institute, Clinics Hospital, University of Sao Paulo Medical School, S\u00e3o Paulo, SP, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heart Institute, Clinics Hospital, University of Sao Paulo Medical School, S\u00e3o Paulo, SP, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085369510","display_name":"Marco A. Guti\u00e9rrez","orcid":"https://orcid.org/0000-0003-0964-6222"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Marco Antonio Gutierrez","raw_affiliation_strings":["Heart Institute, Clinics Hospital, University of Sao Paulo Medical School, S\u00e3o Paulo, SP, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heart Institute, Clinics Hospital, University of Sao Paulo Medical School, S\u00e3o Paulo, SP, Brazil","institution_ids":["https://openalex.org/I17974374"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I17974374"],"apc_list":null,"apc_paid":null,"fwci":8.4058,"has_fulltext":true,"cited_by_count":52,"citation_normalized_percentile":{"value":0.98346757,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"2020","issue":null,"first_page":"1238","last_page":"1241"},"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/T12167","display_name":"Bacterial Identification and Susceptibility Testing","score":0.9829999804496765,"subfield":{"id":"https://openalex.org/subfields/1308","display_name":"Clinical Biochemistry"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10654","display_name":"Pneumonia and Respiratory Infections","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6524903774261475},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6473857760429382},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.5740445256233215},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5673931241035461},{"id":"https://openalex.org/keywords/pneumonia","display_name":"Pneumonia","score":0.5434998273849487},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5405316352844238},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.51894211769104},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.47973647713661194},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.42505186796188354},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.42113491892814636},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.35158389806747437},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.34508222341537476},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3141506314277649},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30489757657051086},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24643364548683167},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.14103779196739197}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6524903774261475},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6473857760429382},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.5740445256233215},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5673931241035461},{"id":"https://openalex.org/C2777914695","wikidata":"https://www.wikidata.org/wiki/Q12192","display_name":"Pneumonia","level":2,"score":0.5434998273849487},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5405316352844238},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.51894211769104},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.47973647713661194},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.42505186796188354},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.42113491892814636},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.35158389806747437},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34508222341537476},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3141506314277649},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30489757657051086},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24643364548683167},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.14103779196739197}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002648","descriptor_name":"Child","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002648","descriptor_name":"Child","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002648","descriptor_name":"Child","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":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011014","descriptor_name":"Pneumonia","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D011014","descriptor_name":"Pneumonia","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D011014","descriptor_name":"Pneumonia","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D013909","descriptor_name":"Thorax","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013909","descriptor_name":"Thorax","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013909","descriptor_name":"Thorax","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc44109.2020.9176517","is_oa":true,"landing_page_url":"https://doi.org/10.1109/embc44109.2020.9176517","pdf_url":"https://ieeexplore.ieee.org/ielx7/9167168/9175149/09176517.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 42nd Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:33018211","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33018211","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":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":{"id":"doi:10.1109/embc44109.2020.9176517","is_oa":true,"landing_page_url":"https://doi.org/10.1109/embc44109.2020.9176517","pdf_url":"https://ieeexplore.ieee.org/ielx7/9167168/9175149/09176517.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 42nd Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8500000238418579,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3081612852.pdf","grobid_xml":"https://content.openalex.org/works/W3081612852.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W2051838543","https://openalex.org/W2098196189","https://openalex.org/W2117539524","https://openalex.org/W2133979383","https://openalex.org/W2611650229","https://openalex.org/W2770241596","https://openalex.org/W2788633781","https://openalex.org/W2884261459","https://openalex.org/W2903686131","https://openalex.org/W2956123709","https://openalex.org/W2963466845","https://openalex.org/W2983407137","https://openalex.org/W2986087452","https://openalex.org/W2986571455","https://openalex.org/W3101156210","https://openalex.org/W4300485340","https://openalex.org/W6637373629","https://openalex.org/W6639824700","https://openalex.org/W6746693533","https://openalex.org/W6765185728"],"related_works":["https://openalex.org/W2952813363","https://openalex.org/W4378678253","https://openalex.org/W2911497689","https://openalex.org/W4360783045","https://openalex.org/W3192962470","https://openalex.org/W3176438653","https://openalex.org/W2770149305","https://openalex.org/W2972076240","https://openalex.org/W3167930666","https://openalex.org/W3014952856"],"abstract_inverted_index":{"Pneumonia":[0],"is":[1,29,40,161],"one":[2],"of":[3,7,18,24,75,201,212,268,302,308,317],"the":[4,16,22,88,115,119,175,178,197,235,248,266,280,315,322],"leading":[5],"causes":[6],"childhood":[8],"mortality":[9],"worldwide.":[10],"Chest":[11],"x-ray":[12],"(CXR)":[13],"can":[14,45,286],"aid":[15,36],"diagnosis":[17],"pneumonia,":[19],"but":[20],"in":[21,50,291],"case":[23],"low":[25,292],"contrast":[26,293],"images,":[27,116],"it":[28,44],"important":[30],"to":[31,35,86,205,216,255,278,296,320],"include":[32],"computational":[33],"tools":[34],"specialists.":[37],"Deep":[38,284],"learning":[39,285],"an":[41],"alternative":[42],"because":[43],"identify":[46,256,287],"patterns":[47,270,290],"automatically,":[48],"even":[49],"low-resolution":[51],"images.":[52],"We":[53,79],"propose":[54],"herein":[55],"a":[56,98,128],"convolutional":[57],"neural":[58],"network":[59],"(CNN)":[60],"architecture":[61],"with":[62,127,182,275,310],"different":[63,82,140],"training":[64,141],"strategies":[65,166],"towards":[66],"detecting":[67],"pneumonia":[68,100,207,297],"on":[69,163],"CXRs":[70,93],"and":[71,77,110,122,137,150,168,190,210,241,252,273,298,304],"distinguishing":[72],"its":[73,124,300],"subforms":[74,301],"bacteria":[76,272,303],"virus.":[78,305],"also":[80],"evaluated":[81,106,138],"image":[83,108,145,148,153],"pre-processing":[84,104],"methods":[85,105],"improve":[87],"classification.":[89],"This":[90],"study":[91],"used":[92,225,234],"from":[94,97,247,271],"pediatric":[95],"patients":[96],"public":[99],"CXR":[101,144,237,258],"dataset.":[102],"The":[103,155,170,192,261,306],"were":[107],"cropping":[109,240],"histogram":[111,242],"equalization.":[112],"To":[113],"classify":[114,206,217],"we":[117,135],"adopted":[118],"VGG16":[120],"CNN":[121],"replaced":[123],"fully-connected":[125],"layers":[126],"customized":[129],"multilayer":[130],"perceptron.":[131],"With":[132],"this":[133],"architecture,":[134],"proposed":[136,262],"four":[139],"strategies:":[142],"original":[143,236],"(baseline),":[146],"chest-cavity-cropped":[147],"(A),":[149],"histogram-equalized":[151],"segmented":[152],"(B).":[154],"last":[156],"strategy":[157],"method":[158],"(C)":[159],"implemented":[160],"based":[162],"ensemble":[164,193,263],"between":[165],"A":[167],"B.":[169],"performance":[171],"was":[172,253],"assessed":[173],"by":[174],"area":[176],"under":[177],"ROC":[179],"curve":[180],"(AUC)":[181],"95%":[183],"confidence":[184],"interval":[185],"(CI),":[186],"accuracy,":[187],"sensitivity,":[188],"specificity,":[189],"F1-score.":[191],"model":[194,264],"C":[195],"yielded":[196],"highest":[198],"performances:":[199],"AUC":[200,211,230],"0.97":[202],"(CI:":[203,214],"0.96-0.99)":[204],"vs.":[208,219],"normal,":[209],"0.91":[213],"0.88-0.94)":[215],"bacterial":[218],"viral":[220],"cases.":[221],"All":[222],"models":[223],"that":[224],"pre-processed":[226],"images":[227,294],"showed":[228],"higher":[229],"than":[231],"baseline,":[232],"which":[233],"image.":[238],"Image":[239],"equalization":[243],"reduced":[244],"irrelevant":[245],"information":[246],"exam,":[249],"enhanced":[250],"contrast,":[251],"able":[254],"fine":[257],"texture":[259],"details.":[260],"increased":[265],"representation":[267],"inflammatory":[269],"viruses":[274],"few":[276],"epochs":[277],"train":[279],"deep":[281],"CNNs.Clinical":[282],"relevance-":[283],"complex":[288],"radiographic":[289],"due":[295],"distinguish":[299],"correlation":[307],"imaging":[309],"lab":[311],"results":[312],"could":[313],"accelerate":[314],"adoption":[316],"complementary":[318],"exams":[319],"confirm":[321],"disease's":[323],"cause.":[324]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
