{"id":"https://openalex.org/W3089920065","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206678","title":"DeepConsensus: Consensus-based Interpretable Deep Neural Networks with Application to Mortality Prediction","display_name":"DeepConsensus: Consensus-based Interpretable Deep Neural Networks with Application to Mortality Prediction","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3089920065","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206678","mag":"3089920065","pmid":"https://pubmed.ncbi.nlm.nih.gov/33101768"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9206678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206678","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":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7583142","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028569628","display_name":"Shaeke Salman","orcid":null},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaeke Salman","raw_affiliation_strings":["Department of Computer Science, Florida State University, FL 32306, USA","Department of Computer Science, Florida State University, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Florida State University, FL 32306, USA","institution_ids":["https://openalex.org/I103163165"]},{"raw_affiliation_string":"Department of Computer Science, Florida State University, FL, USA","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012198181","display_name":"Seyedeh Neelufar Payrovnaziri","orcid":"https://orcid.org/0000-0003-4712-9648"},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Seyedeh Neelufar Payrovnaziri","raw_affiliation_strings":["School of Information, Florida State University, FL 32306, USA","School of Information, Florida State University, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information, Florida State University, FL 32306, USA","institution_ids":["https://openalex.org/I103163165"]},{"raw_affiliation_string":"School of Information, Florida State University, FL, USA","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102867647","display_name":"Xiuwen Liu","orcid":"https://orcid.org/0000-0002-9320-3872"},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiuwen Liu","raw_affiliation_strings":["Department of Computer Science, Florida State University, FL 32306, USA","Department of Computer Science, Florida State University, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Florida State University, FL 32306, USA","institution_ids":["https://openalex.org/I103163165"]},{"raw_affiliation_string":"Department of Computer Science, Florida State University, FL, USA","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068745733","display_name":"Pablo Rengifo\u2010Moreno","orcid":null},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]},{"id":"https://openalex.org/I1323276237","display_name":"Florida A&M University - Florida State University College of Engineering","ror":"https://ror.org/01v4tq883","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165","https://openalex.org/I1323276237","https://openalex.org/I8248082"]},{"id":"https://openalex.org/I94062374","display_name":"Florida College","ror":"https://ror.org/010bgev76","country_code":"US","type":"education","lineage":["https://openalex.org/I94062374"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pablo Rengifo-Moreno","raw_affiliation_strings":["College of Medicine, Florida State University, FL 32306, USA","College of Medicine, Florida State University, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Medicine, Florida State University, FL 32306, USA","institution_ids":["https://openalex.org/I103163165","https://openalex.org/I94062374","https://openalex.org/I1323276237"]},{"raw_affiliation_string":"College of Medicine, Florida State University, FL, USA","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047567293","display_name":"Zhe He","orcid":"https://orcid.org/0000-0003-3608-0244"},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhe He","raw_affiliation_strings":["School of Information, Florida State University, FL 32306, USA","School of Information, Florida State University, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information, Florida State University, FL 32306, USA","institution_ids":["https://openalex.org/I103163165"]},{"raw_affiliation_string":"School of Information, Florida State University, FL, USA","institution_ids":["https://openalex.org/I103163165"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8126,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.79431439,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"abs 1611 3530","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":0.9993000030517578,"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":0.9993000030517578,"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":0.9988999962806702,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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":0.9632803201675415},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7486456036567688},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.703174352645874},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6571947336196899},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6328365206718445},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.623153567314148},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5777401328086853},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5625536441802979},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48749446868896484},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.4576202630996704},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4558703601360321},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3482857346534729},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12711137533187866}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9632803201675415},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7486456036567688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.703174352645874},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6571947336196899},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6328365206718445},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.623153567314148},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5777401328086853},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5625536441802979},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48749446868896484},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.4576202630996704},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4558703601360321},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3482857346534729},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12711137533187866},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9206678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206678","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":"pmid:33101768","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33101768","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":"Proceedings of ... International Joint Conference on Neural Networks. International Joint Conference on Neural Networks","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:7583142","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7583142","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc Int Jt Conf Neural Netw","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:7583142","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7583142","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc Int Jt Conf Neural Netw","raw_type":"Text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8299999833106995,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G6111815890","display_name":null,"funder_award_id":"R21 AG061431","funder_id":"https://openalex.org/F4320337337","funder_display_name":"National Institute on Aging"},{"id":"https://openalex.org/G7612683197","display_name":null,"funder_award_id":"UL1 TR001427","funder_id":"https://openalex.org/F4320337472","funder_display_name":"National Center for Advancing Translational Sciences"}],"funders":[{"id":"https://openalex.org/F4320337337","display_name":"National Institute on Aging","ror":"https://ror.org/049v75w11"},{"id":"https://openalex.org/F4320337472","display_name":"National Center for Advancing Translational Sciences","ror":"https://ror.org/04pw6fb54"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W1582447064","https://openalex.org/W1945616565","https://openalex.org/W2112796928","https://openalex.org/W2166950143","https://openalex.org/W2282821441","https://openalex.org/W2346834216","https://openalex.org/W2396881363","https://openalex.org/W2484192585","https://openalex.org/W2594475271","https://openalex.org/W2594633041","https://openalex.org/W2597603852","https://openalex.org/W2607306668","https://openalex.org/W2609731728","https://openalex.org/W2621615146","https://openalex.org/W2625625371","https://openalex.org/W2731468224","https://openalex.org/W2764024122","https://openalex.org/W2791453970","https://openalex.org/W2807299122","https://openalex.org/W2809671526","https://openalex.org/W2810174094","https://openalex.org/W2883817443","https://openalex.org/W2888487581","https://openalex.org/W2891503716","https://openalex.org/W2892986808","https://openalex.org/W2900103278","https://openalex.org/W2912626019","https://openalex.org/W2919115771","https://openalex.org/W2930304691","https://openalex.org/W2949495270","https://openalex.org/W2951885001","https://openalex.org/W2956993847","https://openalex.org/W2962851944","https://openalex.org/W2962862931","https://openalex.org/W2962957673","https://openalex.org/W2963207607","https://openalex.org/W2963486721","https://openalex.org/W2970330753","https://openalex.org/W2980642662","https://openalex.org/W2996061341","https://openalex.org/W3104523752","https://openalex.org/W3118608800","https://openalex.org/W3137695714","https://openalex.org/W4211143906","https://openalex.org/W4289293816","https://openalex.org/W6640425456","https://openalex.org/W6685133223","https://openalex.org/W6734194636","https://openalex.org/W6735632633","https://openalex.org/W6737136810","https://openalex.org/W6737947904","https://openalex.org/W6738988723","https://openalex.org/W6741194474","https://openalex.org/W6752343131","https://openalex.org/W6753024113","https://openalex.org/W6753648707","https://openalex.org/W6755034403","https://openalex.org/W6757095722","https://openalex.org/W6759044113","https://openalex.org/W6763485134","https://openalex.org/W6765650036","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2797441709","https://openalex.org/W2346578521","https://openalex.org/W4283692230","https://openalex.org/W4297660007","https://openalex.org/W2886918272","https://openalex.org/W4387589990","https://openalex.org/W3203722024","https://openalex.org/W2943982549","https://openalex.org/W3101055019","https://openalex.org/W4241566321"],"abstract_inverted_index":{"Deep":[0],"neural":[1,68,105,113,176],"networks":[2,17,69],"have":[3],"achieved":[4],"remarkable":[5],"success":[6],"in":[7,136,165],"various":[8],"challenging":[9],"tasks.":[10],"However,":[11],"the":[12,29,61,91,109,141,160,168,172,187,203],"black-box":[13],"nature":[14],"of":[15,31,64,66,111,119,143,162,174],"such":[16,24,54,197],"is":[18,78,94],"not":[19,48],"acceptable":[20],"to":[21,37,50,80,96,130],"critical":[22],"applications,":[23],"as":[25,193,198],"healthcare.":[26],"In":[27,56,184],"particular,":[28,185],"existence":[30],"adversarial":[32,81],"examples":[33,82],"and":[34,70,83,122,146,171],"their":[35],"overgeneralization":[36],"irrelevant,":[38],"out-ofdistribution":[39],"inputs":[40],"with":[41],"high":[42],"confidence":[43],"makes":[44],"it":[45,201],"difficult,":[46],"if":[47],"impossible,":[49],"explain":[51],"decisions":[52],"by":[53,100,140],"networks.":[55,106],"this":[57],"paper,":[58],"we":[59,115],"analyze":[60],"underlying":[62],"mechanism":[63],"generalization":[65],"deep":[67,104,112,175],"propose":[71],"an":[72,156],"(n,":[73],"k)":[74],"consensus":[75,92],"algorithm":[76,93,164],"which":[77],"insensitive":[79],"can":[84],"reliably":[85],"reject":[86],"out-":[87],"of-distribution":[88],"samples.":[89],"Furthermore,":[90],"able":[95],"improve":[97],"classification":[98],"accuracy":[99,170,205],"using":[101],"multiple":[102],"trained":[103],"To":[107],"handle":[108],"complexity":[110],"networks,":[114],"cluster":[116],"linear":[117],"approximations":[118],"individual":[120],"models":[121,129,149,178,196],"identify":[123],"highly":[124],"correlated":[125],"clusters":[126],"among":[127],"different":[128],"capture":[131],"feature":[132],"importance":[133,142],"robustly,":[134],"resulting":[135],"improved":[137],"interpretability.":[138],"Motivated":[139],"building":[144],"accurate":[145],"interpretable":[147],"prediction":[148,169,204],"for":[150],"healthcare,":[151],"our":[152,163],"experimental":[153],"results":[154],"on":[155,179],"ICU":[157],"dataset":[158],"show":[159],"effectiveness":[161],"enhancing":[166],"both":[167],"interpretability":[173,192],"network":[177],"one-year":[180],"patient":[181],"mortality":[182],"prediction.":[183],"while":[186],"proposed":[188],"method":[189],"maintains":[190],"similar":[191],"conventional":[194],"shallow":[195],"logistic":[199],"regression,":[200],"improves":[202],"significantly.":[206]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4}],"updated_date":"2026-06-24T13:16:06.693445","created_date":"2025-10-10T00:00:00"}