{"id":"https://openalex.org/W4417250532","doi":"https://doi.org/10.1109/bibe66822.2025.00110","title":"Decoding EEG Signals to Predict SSRI Therapy Success in Depression Using Automated Tunable Q-Factor Wavelet Transform and Centered Correntropy","display_name":"Decoding EEG Signals to Predict SSRI Therapy Success in Depression Using Automated Tunable Q-Factor Wavelet Transform and Centered Correntropy","publication_year":2025,"publication_date":"2025-11-06","ids":{"openalex":"https://openalex.org/W4417250532","doi":"https://doi.org/10.1109/bibe66822.2025.00110"},"language":null,"primary_location":{"id":"doi:10.1109/bibe66822.2025.00110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibe66822.2025.00110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 25th International Conference on Bioinformatics and Bioengineering (BIBE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072367224","display_name":"Hesam Akbari","orcid":"https://orcid.org/0000-0002-9746-4981"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hesam Akbari","raw_affiliation_strings":["University of North Texas,Department of Information Science,Denton,TX,USA"],"affiliations":[{"raw_affiliation_string":"University of North Texas,Department of Information Science,Denton,TX,USA","institution_ids":["https://openalex.org/I123534392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030314469","display_name":"Ram Bilas Pachori","orcid":"https://orcid.org/0000-0002-6061-4309"},"institutions":[{"id":"https://openalex.org/I64295750","display_name":"Indian Institute of Technology Indore","ror":"https://ror.org/01hhf7w52","country_code":"IN","type":"education","lineage":["https://openalex.org/I64295750"]},{"id":"https://openalex.org/I33003672","display_name":"Indian Institute of Management Indore","ror":"https://ror.org/02j8pmw82","country_code":"IN","type":"education","lineage":["https://openalex.org/I33003672"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ram Bilas Pachori","raw_affiliation_strings":["Indian Institute of Technology Indore,Department of Electrical Engineering,Indore,Madhya Pradesh,India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Indore,Department of Electrical Engineering,Indore,Madhya Pradesh,India","institution_ids":["https://openalex.org/I64295750","https://openalex.org/I33003672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046182499","display_name":"Mutlu Mete","orcid":"https://orcid.org/0000-0003-0600-8073"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mutlu Mete","raw_affiliation_strings":["University of North Texas,Department of Information Science,Denton,TX,USA"],"affiliations":[{"raw_affiliation_string":"University of North Texas,Department of Information Science,Denton,TX,USA","institution_ids":["https://openalex.org/I123534392"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5072367224"],"corresponding_institution_ids":["https://openalex.org/I123534392"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.42132601,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"635","last_page":"639"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.925599992275238,"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"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.925599992275238,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.017400000244379044,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.016300000250339508,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.5830000042915344},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.531499981880188},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.41350001096725464},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4009000062942505},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.3610999882221222},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.35760000348091125},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.34790000319480896},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.3425999879837036},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.3280999958515167}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7689999938011169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6378999948501587},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.5830000042915344},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.531499981880188},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41839998960494995},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.41350001096725464},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4009000062942505},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.3610999882221222},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.35760000348091125},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.34790000319480896},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.3425999879837036},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3280999958515167},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2847999930381775},{"id":"https://openalex.org/C38858127","wikidata":"https://www.wikidata.org/wiki/Q5441228","display_name":"Feed forward","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2808000147342682},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.27950000762939453},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.2754000127315521},{"id":"https://openalex.org/C2777669559","wikidata":"https://www.wikidata.org/wiki/Q407617","display_name":"Sertraline","level":4,"score":0.27469998598098755},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C100515483","wikidata":"https://www.wikidata.org/wiki/Q3268235","display_name":"Filter bank","level":3,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibe66822.2025.00110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibe66822.2025.00110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 25th International Conference on Bioinformatics and Bioengineering (BIBE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2112797878","https://openalex.org/W2584523198","https://openalex.org/W3040413318","https://openalex.org/W3129391793","https://openalex.org/W3176218226","https://openalex.org/W4296079594","https://openalex.org/W4391840915","https://openalex.org/W4405415459","https://openalex.org/W4409625234"],"related_works":[],"abstract_inverted_index":{"Depression,":[0],"a":[1,59,146,194,204,209],"prevalent":[2],"mental":[3],"disorder,":[4],"can":[5],"have":[6],"severe":[7],"consequences":[8],"if":[9],"left":[10],"untreated,":[11],"including":[12],"self-harm":[13],"and":[14,73,79,87,102,170,186,208,244,260,285],"suicide.":[15],"Selective":[16],"Serotonin":[17],"Reuptake":[18],"Inhibitors":[19],"(SSRI)":[20],"therapy":[21,35,235,254,287],"is":[22,71,150,178,213],"the":[23,54,154,159,184,187,220,247,257],"first":[24],"course":[25],"of":[26,33,68,156,162,230],"treatment":[27,44],"for":[28,62,110,129,251,274,289],"depression":[29,267],"disorder.":[30],"Accurate":[31],"prediction":[32],"SSRI":[34,234,253],"outcomes":[36],"could":[37],"significantly":[38],"assist":[39],"medical":[40,276],"professionals":[41],"in":[42,219,232,266,278],"tailoring":[43],"plans":[45,288],"to":[46,93,99,135,152,166,180,215,281],"individual":[47],"subjects.":[48],"Electroencephalography":[49],"(EEG)":[50],"signals,":[51],"which":[52,133],"reflect":[53],"brain's":[55],"neural":[56,206],"activity,":[57],"offer":[58],"non-invasive":[60],"avenue":[61],"such":[63],"predictions.":[64],"However,":[65],"visual":[66],"analysis":[67],"EEG":[69,82,90],"signals":[70,83,91],"laborious":[72],"time-consuming,":[74],"given":[75],"their":[76],"complex,":[77,85],"nonlinear,":[78,86],"nonstationary":[80],"nature.":[81],"are":[84,191,200,246,263],"nonstationary.":[88],"Consequently,":[89],"need":[92],"be":[94],"decomposed":[95],"into":[96],"several":[97],"sub-bands":[98,169],"extract":[100,167],"detailed":[101],"representative":[103],"information.":[104],"Traditional":[105],"manual":[106],"filter":[107],"bank":[108],"design":[109],"decomposition":[111],"risks":[112],"information":[113,138],"loss.":[114],"To":[115],"address":[116],"this":[117,119],"challenge,":[118],"study":[120],"proposes":[121],"an":[122,226],"automated":[123],"tunable-Q":[124],"wavelet":[125],"transform":[126],"(ATQWT)":[127],"framework":[128],"automatic":[130,160],"signal":[131,172],"decomposition,":[132],"aims":[134],"preserve":[136],"critical":[137],"during":[139,174],"analysis.":[140],"The":[141,222],"Starfish":[142],"optimization":[143],"algorithm":[144],"(SFOA),":[145],"bio-inspired":[147],"metaheuristic":[148],"approach,":[149],"employed":[151],"optimize":[153],"parameters":[155,165],"ATQWT,":[157],"facilitating":[158],"selection":[161],"optimal":[163],"tuning":[164],"meaningful":[168],"enhance":[171],"reconstruction":[173],"synthesis.":[175],"Centered":[176],"correntropy":[177],"utilized":[179],"compute":[181],"features":[182,190,199],"from":[183],"sub-bands,":[185],"most":[188,248],"discriminative":[189],"identified":[192],"using":[193,203],"nearest":[195],"neighbor":[196],"algorithm.":[197],"These":[198],"then":[201],"classified":[202],"feedforward":[205],"network,":[207],"10-fold":[210],"cross-validation":[211],"strategy":[212],"implemented":[214],"mitigate":[216],"potential":[217,273],"bias":[218],"results.":[221],"proposed":[223],"method":[224],"achieves":[225],"outstanding":[227],"classification":[228],"accuracy":[229],"99.36%":[231],"predicting":[233,252],"outcomes.":[236,255],"Results":[237],"show":[238],"F4,":[239],"P4,":[240],"C4,":[241],"Fp2,":[242],"F8":[243],"Fz":[245],"informative":[249],"channels":[250],"So,":[256],"right-lateralized":[258],"prefrontal":[259],"parietal":[261],"lobes":[262],"more":[264,283],"involved":[265],"therapy.":[268],"This":[269],"approach":[270],"holds":[271],"significant":[272],"assisting":[275],"teams":[277],"clinical":[279],"settings":[280],"develop":[282],"personalized":[284],"effective":[286],"subjects":[290],"with":[291],"depression.":[292]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-12-11T00:00:00"}
