{"id":"https://openalex.org/W3020085867","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206837","title":"Explainable Deep CNNs for MRI-Based Diagnosis of Alzheimer\u2019s Disease","display_name":"Explainable Deep CNNs for MRI-Based Diagnosis of Alzheimer\u2019s Disease","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3020085867","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206837","mag":"3020085867"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9206837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2004.12204","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056283710","display_name":"Eduardo Nigri","orcid":null},"institutions":[{"id":"https://openalex.org/I110200422","display_name":"Universidade Federal de Minas Gerais","ror":"https://ror.org/0176yjw32","country_code":"BR","type":"education","lineage":["https://openalex.org/I110200422"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Eduardo Nigri","raw_affiliation_strings":["CS Dept, UFMG & Kunumi, Belo Horizonte, Brazil","UFMG & Kunumi,CS Dept@,Belo Horizonte,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CS Dept, UFMG & Kunumi, Belo Horizonte, Brazil","institution_ids":["https://openalex.org/I110200422"]},{"raw_affiliation_string":"UFMG & Kunumi,CS Dept@,Belo Horizonte,Brazil","institution_ids":["https://openalex.org/I110200422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067195269","display_name":"N\u00edvio Ziviani","orcid":"https://orcid.org/0000-0002-7079-2010"},"institutions":[{"id":"https://openalex.org/I110200422","display_name":"Universidade Federal de Minas Gerais","ror":"https://ror.org/0176yjw32","country_code":"BR","type":"education","lineage":["https://openalex.org/I110200422"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Nivio Ziviani","raw_affiliation_strings":["CS Dept, UFMG & Kunumi, Belo Horizonte, Brazil","UFMG & Kunumi,CS Dept@,Belo Horizonte,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CS Dept, UFMG & Kunumi, Belo Horizonte, Brazil","institution_ids":["https://openalex.org/I110200422"]},{"raw_affiliation_string":"UFMG & Kunumi,CS Dept@,Belo Horizonte,Brazil","institution_ids":["https://openalex.org/I110200422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051958513","display_name":"F\u00e1bio A. M. Cappabianco","orcid":"https://orcid.org/0000-0002-2139-7938"},"institutions":[{"id":"https://openalex.org/I4210090944","display_name":"Funda\u00e7\u00e3o de Apoio \u00e0 Universidade Federal de S\u00e3o Paulo","ror":"https://ror.org/00bkgf580","country_code":"BR","type":"other","lineage":["https://openalex.org/I4210090944"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Fabio Cappabianco","raw_affiliation_strings":["UNIFESP DCT, S\u00e3o Jos\u00e9 dos Campos, Brazil","UNIFESP DCT,S\u00e3o Jos\u00e9 dos Campos,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UNIFESP DCT, S\u00e3o Jos\u00e9 dos Campos, Brazil","institution_ids":["https://openalex.org/I4210090944"]},{"raw_affiliation_string":"UNIFESP DCT,S\u00e3o Jos\u00e9 dos Campos,Brazil","institution_ids":["https://openalex.org/I4210090944"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063008030","display_name":"Augusto Antunes","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Augusto Antunes","raw_affiliation_strings":["InRad-FMUSP & Kunumi, S\u00e3o Paulo, Brazil","InRad-FMUSP & Kunumi,S\u00e3o Paulo,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"InRad-FMUSP & Kunumi, S\u00e3o Paulo, Brazil","institution_ids":[]},{"raw_affiliation_string":"InRad-FMUSP & Kunumi,S\u00e3o Paulo,Brazil","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086714399","display_name":"Adriano Veloso","orcid":"https://orcid.org/0000-0002-9177-4954"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Adriano Veloso","raw_affiliation_strings":["CS Dept, UFMG, Belo Horizonte, Brazil","UFMG,CS Dept,Belo Horizonte,Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CS Dept, UFMG, Belo Horizonte, Brazil","institution_ids":[]},{"raw_affiliation_string":"UFMG,CS Dept,Belo Horizonte,Brazil","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1334,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5324532,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9959999918937683,"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"}},"topics":[{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9959999918937683,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9957000017166138,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9847999811172485,"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/interpretability","display_name":"Interpretability","score":0.9662085175514221},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.708267092704773},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.704633355140686},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6765056848526001},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6416004300117493},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.5566554069519043},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48981472849845886},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4886973202228546},{"id":"https://openalex.org/keywords/neuroimaging","display_name":"Neuroimaging","score":0.4338940978050232},{"id":"https://openalex.org/keywords/swap","display_name":"Swap (finance)","score":0.4315229058265686},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34941911697387695},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.15879717469215393},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.14674267172813416}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9662085175514221},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.708267092704773},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.704633355140686},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6765056848526001},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6416004300117493},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.5566554069519043},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48981472849845886},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4886973202228546},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.4338940978050232},{"id":"https://openalex.org/C99821215","wikidata":"https://www.wikidata.org/wiki/Q1136583","display_name":"Swap (finance)","level":2,"score":0.4315229058265686},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34941911697387695},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.15879717469215393},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.14674267172813416},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9206837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2004.12204","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2004.12204","pdf_url":"https://arxiv.org/pdf/2004.12204","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2004.12204","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2004.12204","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"},{"id":"mag:3020085867","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2004.12204","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2004.12204","pdf_url":"https://arxiv.org/pdf/2004.12204","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3020085867.pdf","grobid_xml":"https://content.openalex.org/works/W3020085867.grobid-xml"},"referenced_works_count":68,"referenced_works":["https://openalex.org/W1484880041","https://openalex.org/W1686810756","https://openalex.org/W1787224781","https://openalex.org/W1849277567","https://openalex.org/W2008301592","https://openalex.org/W2038003677","https://openalex.org/W2057536936","https://openalex.org/W2079224581","https://openalex.org/W2084358449","https://openalex.org/W2112796928","https://openalex.org/W2112902823","https://openalex.org/W2132587081","https://openalex.org/W2135011268","https://openalex.org/W2148726987","https://openalex.org/W2157633021","https://openalex.org/W2159037096","https://openalex.org/W2163605009","https://openalex.org/W2171225117","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2316116400","https://openalex.org/W2473282638","https://openalex.org/W2493343568","https://openalex.org/W2538556778","https://openalex.org/W2559903050","https://openalex.org/W2580596898","https://openalex.org/W2605409611","https://openalex.org/W2619410643","https://openalex.org/W2626967530","https://openalex.org/W2657631929","https://openalex.org/W2732154503","https://openalex.org/W2734534155","https://openalex.org/W2735045133","https://openalex.org/W2743008510","https://openalex.org/W2751283915","https://openalex.org/W2766059307","https://openalex.org/W2770241596","https://openalex.org/W2772836221","https://openalex.org/W2789360655","https://openalex.org/W2789488272","https://openalex.org/W2806555584","https://openalex.org/W2896496692","https://openalex.org/W2913062164","https://openalex.org/W2949586143","https://openalex.org/W2950651700","https://openalex.org/W2955692055","https://openalex.org/W2956993163","https://openalex.org/W2962851944","https://openalex.org/W2962858109","https://openalex.org/W2964121744","https://openalex.org/W2964131393","https://openalex.org/W2969945254","https://openalex.org/W2977883299","https://openalex.org/W3102603928","https://openalex.org/W3160693705","https://openalex.org/W4300787417","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6639204139","https://openalex.org/W6684191040","https://openalex.org/W6685133223","https://openalex.org/W6687483927","https://openalex.org/W6736518430","https://openalex.org/W6739651123","https://openalex.org/W6743693654","https://openalex.org/W6746693533","https://openalex.org/W6766816269","https://openalex.org/W6794825017"],"related_works":["https://openalex.org/W3090465856","https://openalex.org/W3194386279","https://openalex.org/W1575271607","https://openalex.org/W3155555028","https://openalex.org/W3104971239","https://openalex.org/W3100125480","https://openalex.org/W2483198639","https://openalex.org/W2907148404","https://openalex.org/W2996016606","https://openalex.org/W2948862171","https://openalex.org/W2316116400","https://openalex.org/W3178390372","https://openalex.org/W3041993914","https://openalex.org/W3173366974","https://openalex.org/W3193234348","https://openalex.org/W3206139387","https://openalex.org/W2477263588","https://openalex.org/W2921693280","https://openalex.org/W2981055130"],"abstract_inverted_index":{"Deep":[0],"Convolutional":[1],"Neural":[2],"Networks":[3],"(CNNs)":[4],"are":[5,129,196],"becoming":[6],"prominent":[7],"models":[8,28,52],"for":[9,48,69,105,136,160],"semi-automated":[10],"diagnosis":[11,163],"of":[12,56,72,125,132,164,191,198],"Alzheimer's":[13],"Disease":[14],"(AD)":[15],"using":[16,148,166,175],"brain":[17,73,107,127],"Magnetic":[18],"Resonance":[19],"Imaging":[20],"(MRI).":[21],"Although":[22],"being":[23],"highly":[24],"accurate,":[25],"deep":[26,50,192],"CNN":[27],"lack":[29],"transparency":[30],"and":[31,37],"interpretability,":[32],"precluding":[33],"adequate":[34],"clinical":[35],"reasoning":[36],"not":[38],"complying":[39],"with":[40],"most":[41,130],"current":[42],"regulatory":[43],"demands.":[44],"One":[45],"popular":[46],"choice":[47],"explaining":[49,161],"image":[51,58],"is":[53,102,157],"occluding":[54,70],"regions":[55],"the":[57,64,78,82,106,123,126,137,154,162,169,187],"to":[59,80,89,115,144],"isolate":[60],"their":[61],"influence":[62],"on":[63],"prediction.":[65],"However,":[66],"existing":[67],"methods":[68],"patches":[71],"scans":[74],"generate":[75],"images":[76],"outside":[77],"distribution":[79],"which":[81,112],"model":[83],"was":[84,172],"trained":[85],"for,":[86],"thus":[87],"leading":[88],"unreliable":[90],"explanations.":[91],"In":[92],"this":[93],"paper,":[94],"we":[95,113,181],"propose":[96],"an":[97,149],"alternative":[98],"explanation":[99],"method":[100,156,184],"that":[101,121,128,153,195],"specifically":[103],"designed":[104],"scan":[108],"task.":[109],"Our":[110],"method,":[111],"refer":[114],"as":[116],"Swap":[117],"Test,":[118],"produces":[119],"heatmaps":[120],"depict":[122],"areas":[124],"indicative":[131],"AD,":[133],"providing":[134],"interpretability":[135],"model's":[138],"decisions":[139],"in":[140],"a":[141,176],"format":[142],"understandable":[143],"clinicians.":[145],"Experimental":[146],"results":[147],"axiomatic":[150],"evaluation":[151],"show":[152],"proposed":[155],"more":[158],"suitable":[159],"AD":[165],"MRI":[167],"while":[168],"opposite":[170],"trend":[171],"observed":[173],"when":[174],"typical":[177],"occlusion":[178],"test.":[179],"Therefore,":[180],"believe":[182],"our":[183],"may":[185],"address":[186],"inherent":[188],"black-box":[189],"nature":[190],"neural":[193],"networks":[194],"capable":[197],"diagnosing":[199],"AD.":[200]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-01T08:55:40.977307","created_date":"2025-10-10T00:00:00"}
