{"id":"https://openalex.org/W4361007903","doi":"https://doi.org/10.3390/e25040573","title":"Information Entropy Measures for Evaluation of Reliability of Deep Neural Network Results","display_name":"Information Entropy Measures for Evaluation of Reliability of Deep Neural Network Results","publication_year":2023,"publication_date":"2023-03-27","ids":{"openalex":"https://openalex.org/W4361007903","doi":"https://doi.org/10.3390/e25040573","pmid":"https://pubmed.ncbi.nlm.nih.gov/37190360"},"language":"en","primary_location":{"id":"doi:10.3390/e25040573","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e25040573","pdf_url":"https://www.mdpi.com/1099-4300/25/4/573/pdf?version=1680070838","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/25/4/573/pdf?version=1680070838","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109433155","display_name":"Elakkat D. Gireesh","orcid":null},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]},{"id":"https://openalex.org/I2799648416","display_name":"AdventHealth Orlando","ror":"https://ror.org/02n1cyj49","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I2799648416"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Elakkat D. Gireesh","raw_affiliation_strings":["Department of Computer Engineering, University of Central Florida, Orlando, FL 32817, USA","Epilepsy Center, AdventHealth, Orlando, FL 32803, USA"],"raw_orcid":"https://orcid.org/0000-0001-5993-7883","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, University of Central Florida, Orlando, FL 32817, USA","institution_ids":["https://openalex.org/I106165777"]},{"raw_affiliation_string":"Epilepsy Center, AdventHealth, Orlando, FL 32803, USA","institution_ids":["https://openalex.org/I2799648416"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016780175","display_name":"Varadraj P. Gurupur","orcid":"https://orcid.org/0000-0001-5723-7998"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Varadaraj P. Gurupur","raw_affiliation_strings":["Department of Computer Engineering, University of Central Florida, Orlando, FL 32817, USA"],"raw_orcid":"https://orcid.org/0000-0001-5723-7998","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, University of Central Florida, Orlando, FL 32817, USA","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5016780175","https://openalex.org/A5109433155"],"corresponding_institution_ids":["https://openalex.org/I106165777","https://openalex.org/I2799648416"],"apc_list":{"value":2600,"currency":"CHF","value_usd":3137},"apc_paid":{"value":2600,"currency":"CHF","value_usd":3137},"fwci":0.7755,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.76410752,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"25","issue":"4","first_page":"573","last_page":"573"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9968000054359436,"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/T10320","display_name":"Neural Networks and Applications","score":0.9968000054359436,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7023006081581116},{"id":"https://openalex.org/keywords/certainty","display_name":"Certainty","score":0.6760818958282471},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6655824780464172},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.6319137811660767},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5516945123672485},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5185114145278931},{"id":"https://openalex.org/keywords/sample-entropy","display_name":"Sample entropy","score":0.46729710698127747},{"id":"https://openalex.org/keywords/kullback\u2013leibler-divergence","display_name":"Kullback\u2013Leibler divergence","score":0.4199554920196533},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41890397667884827},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4179559648036957},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4143889248371124},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3936556577682495},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32274964451789856},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18728923797607422}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7023006081581116},{"id":"https://openalex.org/C7493553","wikidata":"https://www.wikidata.org/wiki/Q1520777","display_name":"Certainty","level":2,"score":0.6760818958282471},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6655824780464172},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.6319137811660767},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5516945123672485},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5185114145278931},{"id":"https://openalex.org/C66696666","wikidata":"https://www.wikidata.org/wiki/Q17105612","display_name":"Sample entropy","level":3,"score":0.46729710698127747},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.4199554920196533},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41890397667884827},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4179559648036957},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4143889248371124},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3936556577682495},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32274964451789856},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18728923797607422},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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":5,"locations":[{"id":"doi:10.3390/e25040573","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e25040573","pdf_url":"https://www.mdpi.com/1099-4300/25/4/573/pdf?version=1680070838","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:37190360","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37190360","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":"Entropy (Basel, Switzerland)","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:10137523","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10137523","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10137523/pdf/entropy-25-00573.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":"Entropy (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:3813bcb81b4f4e07b293bc4c21491866","is_oa":true,"landing_page_url":"https://doaj.org/article/3813bcb81b4f4e07b293bc4c21491866","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":"Entropy, Vol 25, Iss 4, p 573 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/25/4/573/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e25040573","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Entropy; Volume 25; Issue 4; Pages: 573","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e25040573","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e25040573","pdf_url":"https://www.mdpi.com/1099-4300/25/4/573/pdf?version=1680070838","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8299999833106995,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4361007903.pdf"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1504118426","https://openalex.org/W1787224781","https://openalex.org/W1995875735","https://openalex.org/W2032950335","https://openalex.org/W2077204677","https://openalex.org/W2106008945","https://openalex.org/W2240067561","https://openalex.org/W2248220518","https://openalex.org/W2553015255","https://openalex.org/W2562793216","https://openalex.org/W2947459187","https://openalex.org/W2962858109","https://openalex.org/W2963238274","https://openalex.org/W2970085549","https://openalex.org/W3132764260","https://openalex.org/W3155754457","https://openalex.org/W3158577694","https://openalex.org/W3163437202","https://openalex.org/W3177432079","https://openalex.org/W4213194625","https://openalex.org/W4224316937","https://openalex.org/W4234372187","https://openalex.org/W4248273320","https://openalex.org/W4252713891","https://openalex.org/W4255427706","https://openalex.org/W6730042731","https://openalex.org/W6767184030","https://openalex.org/W6793671577"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W4286629047","https://openalex.org/W2962182036","https://openalex.org/W4311734044","https://openalex.org/W2523271418","https://openalex.org/W2498166457","https://openalex.org/W1507664523","https://openalex.org/W2112100270"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"(DNN)":[3],"try":[4],"to":[5,9,94,215,232,236,270,273],"analyze":[6],"given":[7],"data,":[8],"come":[10],"up":[11],"with":[12,186,199],"decisions":[13],"regarding":[14],"the":[15,21,31,39,45,76,79,104,107,112,119,122,131,135,143,151,160,178,181,187,200,205,213,225,233,238,241,251,262,279,283],"inputs.":[16],"The":[17,28,266],"decision-making":[18],"process":[19,62],"of":[20,30,47,49,54,63,83,106,111,124,130,142,166,180,212,227,264],"DNN":[22,58,125,206,276],"model":[23,32,102],"is":[24,73,195,230],"not":[25,172],"entirely":[26],"transparent.":[27],"confidence":[29,263],"predictions":[33,126],"on":[34,75,208],"new":[35],"data":[36,93],"fed":[37],"into":[38],"network":[40],"can":[41,147,221,254],"vary.":[42],"We":[43,65,117,175],"address":[44],"question":[46],"certainty":[48,70,123,184,226,252,267],"decision":[50,229],"making":[51],"and":[52,96,127,138],"adequacy":[53],"information":[55,109,128,209,239,280],"capturing":[56],"by":[57,133],"models":[59],"during":[60],"this":[61,86,169],"decision-making.":[64],"introduce":[66],"a":[67,140,228],"measure":[68],"called":[69],"index,":[71],"which":[72],"based":[74],"outputs":[77],"in":[78,240,260,282],"most":[80,161],"penultimate":[81],"layer":[82],"DNN.":[84,98],"In":[85],"approach,":[87],"we":[88],"employed":[89],"iEEG":[90],"(intracranial":[91],"electroencephalogram)":[92],"train":[95],"test":[97],"When":[99],"arriving":[100,158],"at":[101,159,217],"predictions,":[103],"contribution":[105],"entire":[108,152],"content":[110,129,281],"input":[113],"may":[114],"be":[115,148,155,222,255,271],"important.":[116],"explored":[118],"relationship":[120,182],"between":[121,183],"signal":[132,214],"estimating":[134,261],"sample":[136,153,188,192],"entropy":[137],"using":[139],"heatmap":[141],"signal.":[144,243,284],"While":[145],"it":[146,220],"assumed":[149],"that":[150,177,198,204,224],"must":[154],"utilized":[156],"for":[157],"appropriate":[162],"decisions,":[163],"an":[164],"evaluation":[165],"DNNs":[167],"from":[168],"standpoint":[170],"has":[171],"been":[173],"reported.":[174],"demonstrate":[176],"robustness":[179],"index":[185,253,268],"entropy,":[189],"demonstrated":[190],"through":[191],"entropy-heatmap":[193],"correlation,":[194],"higher":[196],"than":[197],"original":[201,242],"signal,":[202],"indicating":[203],"focuses":[207],"rich":[210],"regions":[211],"arrive":[216],"decisions.":[218],"Therefore,":[219],"concluded":[223],"related":[231,272],"DNN's":[234],"ability":[235],"capture":[237],"Our":[244],"results":[245],"indicate":[246],"that,":[247],"within":[248],"its":[249],"limitations,":[250],"used":[256],"as":[257],"useful":[258],"tool":[259],"predictions.":[265],"appears":[269],"how":[274],"effectively":[275],"heatmaps":[277],"captured":[278]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}