{"id":"https://openalex.org/W4313532499","doi":"https://doi.org/10.1007/s44163-022-00045-1","title":"A multi-output network with U-net enhanced class activation map and robust classification performance for medical imaging analysis","display_name":"A multi-output network with U-net enhanced class activation map and robust classification performance for medical imaging analysis","publication_year":2023,"publication_date":"2023-01-03","ids":{"openalex":"https://openalex.org/W4313532499","doi":"https://doi.org/10.1007/s44163-022-00045-1","pmid":"https://pubmed.ncbi.nlm.nih.gov/40478082"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-022-00045-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-022-00045-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-022-00045-1.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["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":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s44163-022-00045-1.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067461844","display_name":"Jaiden Xuan Schraut","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]},{"id":"https://openalex.org/I4210140958","display_name":"Ann Arbor Center for Independent Living","ror":"https://ror.org/045pcya52","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210140958"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jaiden Xuan Schraut","raw_affiliation_strings":["University of Michigan-Ann Arbor, Ann Arbor, USA","University of Michigan\u2013Ann Arbor, Ann Arbor, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Michigan-Ann Arbor, Ann Arbor, USA","institution_ids":["https://openalex.org/I4210140958","https://openalex.org/I27837315"]},{"raw_affiliation_string":"University of Michigan\u2013Ann Arbor, Ann Arbor, USA","institution_ids":["https://openalex.org/I4210140958","https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051729736","display_name":"Leon Liu","orcid":"https://orcid.org/0000-0003-2080-4869"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]},{"id":"https://openalex.org/I4210140958","display_name":"Ann Arbor Center for Independent Living","ror":"https://ror.org/045pcya52","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210140958"]},{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leon Liu","raw_affiliation_strings":["Columbia University, New York, USA","University of Michigan-Ann Arbor, Ann Arbor, USA","University of Michigan\u2013Ann Arbor, Ann Arbor, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University, New York, USA","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"University of Michigan-Ann Arbor, Ann Arbor, USA","institution_ids":["https://openalex.org/I4210140958","https://openalex.org/I27837315"]},{"raw_affiliation_string":"University of Michigan\u2013Ann Arbor, Ann Arbor, USA","institution_ids":["https://openalex.org/I4210140958","https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043782829","display_name":"Jonathan Gong","orcid":"https://orcid.org/0000-0003-3733-7080"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]},{"id":"https://openalex.org/I4210140958","display_name":"Ann Arbor Center for Independent Living","ror":"https://ror.org/045pcya52","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210140958"]},{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan Gong","raw_affiliation_strings":["Columbia University, New York, USA","University of Michigan-Ann Arbor, Ann Arbor, USA","University of Michigan\u2013Ann Arbor, Ann Arbor, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University, New York, USA","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"University of Michigan-Ann Arbor, Ann Arbor, USA","institution_ids":["https://openalex.org/I4210140958","https://openalex.org/I27837315"]},{"raw_affiliation_string":"University of Michigan\u2013Ann Arbor, Ann Arbor, USA","institution_ids":["https://openalex.org/I4210140958","https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004876143","display_name":"Yiqiao Yin","orcid":"https://orcid.org/0000-0003-1216-4232"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiqiao Yin","raw_affiliation_strings":["Columbia University, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University, New York, USA","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5067461844"],"corresponding_institution_ids":["https://openalex.org/I27837315","https://openalex.org/I4210140958"],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":1.3659,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.8013591,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"3","issue":"1","first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":1.0,"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":1.0,"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":0.9983000159263611,"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":0.9980999827384949,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7281940579414368},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6865917444229126},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6583003997802734},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6519017219543457},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5950559973716736},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5493811368942261},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48483359813690186},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47640836238861084},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4702264964580536},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4551406502723694},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42465803027153015},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.42002102732658386},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.402299702167511},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3869401216506958}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7281940579414368},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6865917444229126},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6583003997802734},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6519017219543457},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5950559973716736},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5493811368942261},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48483359813690186},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47640836238861084},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4702264964580536},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4551406502723694},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42465803027153015},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.42002102732658386},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.402299702167511},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3869401216506958},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/s44163-022-00045-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-022-00045-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-022-00045-1.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["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":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmid:40478082","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40478082","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":"Discover artificial intelligence","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:9808678","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9808678","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC9808678/pdf/44163_2022_Article_45.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":"Discov Artif Intell","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:53f6dacb57b8494a8cf5d7d3c24f0ae2","is_oa":true,"landing_page_url":"https://doaj.org/article/53f6dacb57b8494a8cf5d7d3c24f0ae2","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":"Discover Artificial Intelligence, Vol 3, Iss 1, Pp 1-12 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-022-00045-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-022-00045-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-022-00045-1.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["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":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Partnerships for the goals","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4313532499.pdf"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1484257414","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1994062553","https://openalex.org/W1998473914","https://openalex.org/W2019566532","https://openalex.org/W2112796928","https://openalex.org/W2153583003","https://openalex.org/W2295107390","https://openalex.org/W2602594360","https://openalex.org/W2604272474","https://openalex.org/W3004227146","https://openalex.org/W3010702679","https://openalex.org/W3013277995","https://openalex.org/W3013601031","https://openalex.org/W3030790048","https://openalex.org/W3083161015","https://openalex.org/W3091905774","https://openalex.org/W3114196634","https://openalex.org/W3135057764","https://openalex.org/W3139379779","https://openalex.org/W3164988417","https://openalex.org/W3176469180","https://openalex.org/W3200315682","https://openalex.org/W4205765055","https://openalex.org/W4214539878","https://openalex.org/W6607167723"],"related_works":["https://openalex.org/W2068608913","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3024479225","https://openalex.org/W4323287533","https://openalex.org/W3171371563","https://openalex.org/W4379141755","https://openalex.org/W3003847115"],"abstract_inverted_index":{"Computer":[0],"vision":[1],"in":[2,12,72,156],"medical":[3,30,104],"diagnosis":[4,85,219],"has":[5],"achieved":[6],"a":[7,43,110,115,138,144,194,202,229,235],"high":[8,16],"level":[9],"of":[10,42,55,140,159,164,193,232],"success":[11],"diagnosing":[13],"diseases":[14],"with":[15,45],"accuracy.":[17],"However,":[18],"conventional":[19],"classifiers":[20,185],"that":[21,47,150,204],"produce":[22],"an":[23,124],"image-to-label":[24],"result":[25],"provide":[26,201],"insufficient":[27],"information":[28],"for":[29,118,128,217],"professionals":[31],"to":[32,65,68,90,152,186,200],"judge":[33],"and":[34,40,80,88,100,122,184,208,228,246],"raise":[35],"concerns":[36],"over":[37],"the":[38,70,77,84,94,102,157,162,190,206,239],"trust":[39,216],"reliability":[41],"model":[44,179,224],"results":[46,212],"cannot":[48],"be":[49,66,91],"explained.":[50],"To":[51,96],"gain":[52],"local":[53],"insight":[54,142],"cancerous":[56],"regions,":[57],"separate":[58],"tasks":[59],"such":[60],"as":[61],"imaging":[62],"segmentation":[63,120,182],"needs":[64],"implemented":[67],"aid":[69],"doctors":[71],"treating":[73],"patients":[74],"which":[75,82,113,214,242],"doubles":[76],"training":[78],"time":[79],"costs":[81],"renders":[83],"system":[86],"inefficient":[87],"difficult":[89],"accepted":[92],"by":[93,168],"public.":[95],"tackle":[97],"this":[98,107],"issue":[99],"drive":[101],"AI-first":[103],"solutions":[105],"further,":[106],"paper":[108],"proposes":[109],"multi-output":[111],"network":[112],"follows":[114],"U-Net":[116,223],"architecture":[117],"image":[119,181],"output":[121],"features":[123],"additional":[125],"CNN":[126],"module":[127],"auxiliary":[129],"classification":[130,154,211],"output.":[131],"Class":[132,171],"Activation":[133,172],"Maps":[134],"or":[135],"CAMs":[136],"are":[137],"method":[139],"providing":[141],"into":[143],"convolutional":[145],"neural":[146],"network's":[147],"feature":[148],"maps":[149],"lead":[151],"its":[153],"but":[155],"case":[158],"lung":[160,191],"diseases,":[161],"region":[163,192],"interest":[165],"is":[166],"enhanced":[167],"U-net":[169],"assisted":[170],"Mapping":[173],"(CAM)":[174],"visualization.":[175],"Therefore,":[176],"our":[177],"proposed":[178,222],"combines":[180],"models":[183],"crop":[187],"out":[188],"only":[189],"chest":[195],"X-ray's":[196],"class":[197],"activation":[198],"map":[199],"visualization":[203],"improves":[205],"explainability":[207],"can":[209],"generate":[210],"simultaneously":[213],"builds":[215],"AI-led":[218],"system.":[220],"The":[221],"achieves":[225],"97.72%":[226],"accuracy":[227],"dice":[230],"coefficient":[231],"0.9691":[233],"on":[234],"testing":[236],"data":[237],"from":[238],"COVID-QU-Ex":[240],"Dataset":[241],"includes":[243],"both":[244],"diseased":[245],"healthy":[247],"lungs.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
