{"id":"https://openalex.org/W4385580905","doi":"https://doi.org/10.3389/fncom.2023.1115167","title":"Evaluation of computed tomography images under deep learning in the diagnosis of severe pulmonary infection","display_name":"Evaluation of computed tomography images under deep learning in the diagnosis of severe pulmonary infection","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385580905","doi":"https://doi.org/10.3389/fncom.2023.1115167","pmid":"https://pubmed.ncbi.nlm.nih.gov/37602316"},"language":"en","primary_location":{"id":"doi:10.3389/fncom.2023.1115167","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3389/fncom.2023.1115167","pdf_url":"https://public-pages-files-2025.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2023.1115167/pdf","source":{"id":"https://openalex.org/S19778766","display_name":"Frontiers in Computational Neuroscience","issn_l":"1662-5188","issn":["1662-5188"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computational Neuroscience","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://public-pages-files-2025.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2023.1115167/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075909513","display_name":"Ming Mao","orcid":"https://orcid.org/0000-0002-1787-7218"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]},{"id":"https://openalex.org/I4210146387","display_name":"Guang\u2019anmen Hospital","ror":"https://ror.org/04gjmb875","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210146387"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mao Ming","raw_affiliation_strings":["Department of Infectious Disease, South of Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China","Department of Infectious Disease, South of Guang\u2019anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Infectious Disease, South of Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China","institution_ids":["https://openalex.org/I200296433","https://openalex.org/I4210146387"]},{"raw_affiliation_string":"Department of Infectious Disease, South of Guang\u2019anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China","institution_ids":["https://openalex.org/I200296433","https://openalex.org/I4210146387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100778317","display_name":"Na L\u00fc","orcid":"https://orcid.org/0000-0003-2562-2570"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]},{"id":"https://openalex.org/I4210146387","display_name":"Guang\u2019anmen Hospital","ror":"https://ror.org/04gjmb875","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210146387"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Na Lu","raw_affiliation_strings":["Department of Colorectal Surgery, South of Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China","Department of Colorectal Surgery, South of Guang\u2019anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Colorectal Surgery, South of Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China","institution_ids":["https://openalex.org/I200296433","https://openalex.org/I4210146387"]},{"raw_affiliation_string":"Department of Colorectal Surgery, South of Guang\u2019anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China","institution_ids":["https://openalex.org/I200296433","https://openalex.org/I4210146387"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100374757","display_name":"Wei Qian","orcid":"https://orcid.org/0000-0002-9563-721X"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]},{"id":"https://openalex.org/I4210146387","display_name":"Guang\u2019anmen Hospital","ror":"https://ror.org/04gjmb875","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210146387"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Qian","raw_affiliation_strings":["Department of Intensive Care Unit, South of Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China","Department of Intensive Care Unit, South of Guang\u2019anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Intensive Care Unit, South of Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China","institution_ids":["https://openalex.org/I200296433","https://openalex.org/I4210146387"]},{"raw_affiliation_string":"Department of Intensive Care Unit, South of Guang\u2019anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China","institution_ids":["https://openalex.org/I200296433","https://openalex.org/I4210146387"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100374757"],"corresponding_institution_ids":["https://openalex.org/I200296433","https://openalex.org/I4210146387"],"apc_list":{"value":3295,"currency":"USD","value_usd":3295},"apc_paid":{"value":3295,"currency":"USD","value_usd":3295},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13528408,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":null,"first_page":"1115167","last_page":"1115167"},"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.991599977016449,"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":0.984499990940094,"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/computed-tomography","display_name":"Computed tomography","score":0.5117523670196533},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.5100911259651184},{"id":"https://openalex.org/keywords/pleural-effusion","display_name":"Pleural effusion","score":0.5056073665618896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4857907295227051},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.48321783542633057},{"id":"https://openalex.org/keywords/nuclear-medicine","display_name":"Nuclear medicine","score":0.4673108756542206},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.4537142515182495},{"id":"https://openalex.org/keywords/pneumonia","display_name":"Pneumonia","score":0.43001294136047363},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.3738235831260681},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3497164249420166},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34093183279037476},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.32961761951446533},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2757296562194824},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.24572837352752686},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.13708791136741638}],"concepts":[{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.5117523670196533},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.5100911259651184},{"id":"https://openalex.org/C2779634585","wikidata":"https://www.wikidata.org/wiki/Q1334541","display_name":"Pleural effusion","level":2,"score":0.5056073665618896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4857907295227051},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.48321783542633057},{"id":"https://openalex.org/C2989005","wikidata":"https://www.wikidata.org/wiki/Q214963","display_name":"Nuclear medicine","level":1,"score":0.4673108756542206},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.4537142515182495},{"id":"https://openalex.org/C2777914695","wikidata":"https://www.wikidata.org/wiki/Q12192","display_name":"Pneumonia","level":2,"score":0.43001294136047363},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.3738235831260681},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3497164249420166},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34093183279037476},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.32961761951446533},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2757296562194824},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.24572837352752686},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.13708791136741638}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/fncom.2023.1115167","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3389/fncom.2023.1115167","pdf_url":"https://public-pages-files-2025.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2023.1115167/pdf","source":{"id":"https://openalex.org/S19778766","display_name":"Frontiers in Computational Neuroscience","issn_l":"1662-5188","issn":["1662-5188"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computational Neuroscience","raw_type":"journal-article"},{"id":"pmid:37602316","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37602316","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":"Frontiers in computational neuroscience","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10436326","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10436326","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10436326/pdf/fncom-17-1115167.pdf","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":"Front Comput Neurosci","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:6834447f9dd640f38afe132e99f22659","is_oa":true,"landing_page_url":"https://doaj.org/article/6834447f9dd640f38afe132e99f22659","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Computational Neuroscience, Vol 17 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/fncom.2023.1115167","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3389/fncom.2023.1115167","pdf_url":"https://public-pages-files-2025.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2023.1115167/pdf","source":{"id":"https://openalex.org/S19778766","display_name":"Frontiers in Computational Neuroscience","issn_l":"1662-5188","issn":["1662-5188"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computational Neuroscience","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385580905.pdf","grobid_xml":"https://content.openalex.org/works/W4385580905.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W2553421878","https://openalex.org/W2800806089","https://openalex.org/W2809470868","https://openalex.org/W3013371242","https://openalex.org/W3016250576","https://openalex.org/W3016328037","https://openalex.org/W3016513502","https://openalex.org/W3017201241","https://openalex.org/W3021365959","https://openalex.org/W3024836211","https://openalex.org/W3031776733","https://openalex.org/W3038544108","https://openalex.org/W3040561683","https://openalex.org/W3043327973","https://openalex.org/W3094388274","https://openalex.org/W3095784284","https://openalex.org/W3108591672","https://openalex.org/W3112613501","https://openalex.org/W3115781494","https://openalex.org/W3131729262","https://openalex.org/W3180164722","https://openalex.org/W3189806772","https://openalex.org/W3192851400","https://openalex.org/W3197813001","https://openalex.org/W3200372794","https://openalex.org/W3215026929","https://openalex.org/W4200387295","https://openalex.org/W4210787000"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4313906399","https://openalex.org/W4321487865","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W2318112981","https://openalex.org/W4312417841","https://openalex.org/W4225147082","https://openalex.org/W2778653980"],"abstract_inverted_index":{"This":[0],"work":[1],"aimed":[2],"to":[3,43,65,72,118,245,288],"explore":[4],"the":[5,44,74,81,85,108,112,121,148,159,179,197,207,230,240,246,250,266,276],"diagnostic":[6,152],"value":[7],"of":[8,32,84,107,120,154,174,202,229,253,279],"a":[9,135,143],"deep":[10],"convolutional":[11],"neural":[12],"network":[13],"(CNN)":[14],"combined":[15,64],"with":[16,23,27,35,90,166,283],"computed":[17],"tomography":[18],"(CT)":[19],"images":[20,156,176,204,233,263],"in":[21,128],"patients":[22,34],"severe":[24,36,163,280],"pneumonia":[25,37,164,281],"complicated":[26,38,165,282],"pulmonary":[28,40,167,272,284,291],"infection.":[29],"A":[30],"total":[31],"120":[33],"by":[39],"infection":[41,168,273,292],"admitted":[42],"hospital":[45],"were":[46,63,189,224],"selected":[47],"as":[48],"research":[49],"subjects":[50],"and":[51,60,97,142,184,221,286,293],"underwent":[52],"CT":[53,75,113,155,175,203,232,254,262],"imaging":[54],"scans.":[55],"The":[56,77,104,131,151],"empty":[57],"convolution":[58],"(EC)":[59],"U-net":[61],"phase":[62],"construct":[66],"an":[67],"EC-U-net,":[68],"which":[69,257],"was":[70,115,169,243],"applied":[71],"process":[73],"images.":[76],"results":[78],"showed":[79],"that":[80,119,173],"learning":[82],"rate":[83,182,187],"EC-U-net":[86,109,132,160,208,241,267],"model":[87,110,133,161,209,242,268],"decreased":[88],"substantially":[89,170,190],"increasing":[91],"training":[92,102],"times":[93],"until":[94],"it":[95],"stabilized":[96],"reached":[98],"zero":[99],"after":[100],"40":[101],"times.":[103],"segmentation":[105],"result":[106],"for":[111,125,162,210],"image":[114,255],"very":[116],"similar":[117],"mask":[122],"image,":[123],"except":[124],"some":[126],"deviations":[127],"edge":[129],"segmentation.":[130],"exhibited":[134],"significantly":[136],"smaller":[137],"cross-entropy":[138],"loss":[139],"function":[140],"(CELF)":[141],"higher":[144,171,226],"Dice":[145],"coefficient":[146],"than":[147,172,227],"CNN":[149],"algorithm.":[150],"accuracy":[153],"based":[157,205,264],"on":[158,206,265],"alone,":[177],"while":[178],"false":[180,185],"negative":[181],"(FNR)":[183],"positive":[186,199],"(FPR)":[188],"lower":[191],"(":[192,234],"P":[193,235],"<":[194,236],"0.05).":[195,237],"Moreover,":[196],"true":[198],"rates":[200],"(TPRs)":[201],"patchy":[211],"high-density":[212],"shadows,":[213,218],"diffuse":[214],"ground":[215],"glass":[216],"density":[217],"pleural":[219],"effusion,":[220],"lung":[222],"consolidation":[223],"obviously":[225],"those":[228],"original":[231],"In":[238],"short,":[239],"superior":[244],"traditional":[247],"algorithm":[248],"regarding":[249],"overall":[251],"performance":[252],"segmentation,":[256],"can":[258,269],"be":[259],"clinically":[260],"applied.":[261],"clearly":[270],"display":[271],"lesions,":[274],"improve":[275],"clinical":[277],"diagnosis":[278],"infection,":[285],"help":[287],"screen":[289],"early":[290],"carry":[294],"out":[295],"symptomatic":[296],"treatment.":[297]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}