{"id":"https://openalex.org/W4416799931","doi":"https://doi.org/10.1109/snpd65828.2025.11253527","title":"Schizophrenia Detection using non-Orthogonal Adaptive Constrained Independent Vector Analysis with Multivariate Distribution","display_name":"Schizophrenia Detection using non-Orthogonal Adaptive Constrained Independent Vector Analysis with Multivariate Distribution","publication_year":2025,"publication_date":"2025-06-25","ids":{"openalex":"https://openalex.org/W4416799931","doi":"https://doi.org/10.1109/snpd65828.2025.11253527"},"language":null,"primary_location":{"id":"doi:10.1109/snpd65828.2025.11253527","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd65828.2025.11253527","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/ACIS 29th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","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/A5016458190","display_name":"Ali Algumaei","orcid":"https://orcid.org/0009-0004-6457-6006"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Ali Algumaei","raw_affiliation_strings":["Concordia University,Concordia Institute for Information Systems Engineering,Montreal,Canada"],"affiliations":[{"raw_affiliation_string":"Concordia University,Concordia Institute for Information Systems Engineering,Montreal,Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101773294","display_name":"Muhammad Azam","orcid":"https://orcid.org/0000-0003-1904-7338"},"institutions":[{"id":"https://openalex.org/I86519414","display_name":"Algoma University","ror":"https://ror.org/0131d6623","country_code":"CA","type":"education","lineage":["https://openalex.org/I86519414"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Muhammad Azam","raw_affiliation_strings":["Algoma University,School of Computer Science and Technology,Sault Ste. Marie,Canada"],"affiliations":[{"raw_affiliation_string":"Algoma University,School of Computer Science and Technology,Sault Ste. Marie,Canada","institution_ids":["https://openalex.org/I86519414"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090600716","display_name":"Nizar Bouguila","orcid":"https://orcid.org/0000-0001-7224-7940"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Nizar Bouguila","raw_affiliation_strings":["Concordia University,Concordia Institute for Information Systems Engineering,Montreal,Canada"],"affiliations":[{"raw_affiliation_string":"Concordia University,Concordia Institute for Information Systems Engineering,Montreal,Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5016458190"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.48149898,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"880","last_page":"886"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.745199978351593,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.745199978351593,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.17399999499320984,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.012299999594688416,"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/independent-component-analysis","display_name":"Independent component analysis","score":0.6991999745368958},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6403999924659729},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6345999836921692},{"id":"https://openalex.org/keywords/multivariate-normal-distribution","display_name":"Multivariate normal distribution","score":0.5085999965667725},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.49410000443458557},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4675000011920929},{"id":"https://openalex.org/keywords/component-analysis","display_name":"Component analysis","score":0.4366999864578247},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.4343000054359436},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.42820000648498535}],"concepts":[{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.6991999745368958},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6403999924659729},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6345999836921692},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5609999895095825},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5281999707221985},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.5085999965667725},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.49410000443458557},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4675000011920929},{"id":"https://openalex.org/C2780692498","wikidata":"https://www.wikidata.org/wiki/Q16950721","display_name":"Component analysis","level":2,"score":0.4366999864578247},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.4343000054359436},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.42820000648498535},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3984000086784363},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.3962000012397766},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.3871999979019165},{"id":"https://openalex.org/C38180746","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate analysis","level":2,"score":0.3871000111103058},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32350000739097595},{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.2980000078678131},{"id":"https://openalex.org/C56672385","wikidata":"https://www.wikidata.org/wiki/Q17157111","display_name":"Mixture distribution","level":3,"score":0.288100004196167},{"id":"https://openalex.org/C2776412080","wikidata":"https://www.wikidata.org/wiki/Q7431605","display_name":"Schizophrenia (object-oriented programming)","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26249998807907104},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.2605000138282776},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/snpd65828.2025.11253527","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd65828.2025.11253527","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/ACIS 29th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1582893002","https://openalex.org/W2007213925","https://openalex.org/W2017236761","https://openalex.org/W2061174746","https://openalex.org/W2127851351","https://openalex.org/W2152049961","https://openalex.org/W2172045185","https://openalex.org/W2337323496","https://openalex.org/W2437182874","https://openalex.org/W2663135018","https://openalex.org/W2792612132","https://openalex.org/W2796117273","https://openalex.org/W2913356243","https://openalex.org/W2913406796","https://openalex.org/W2962785568","https://openalex.org/W2973007151","https://openalex.org/W3015233996","https://openalex.org/W3037801514","https://openalex.org/W3217421674","https://openalex.org/W4281392886","https://openalex.org/W4313471344","https://openalex.org/W4318975584","https://openalex.org/W4321788863","https://openalex.org/W4367675017"],"related_works":[],"abstract_inverted_index":{"Advancements":[0],"in":[1,56,129],"blind":[2],"source":[3],"separation":[4],"(BSS)":[5],"techniques":[6],"have":[7],"significantly":[8],"improved":[9],"the":[10,43,49,74,97,107,114,120,123],"ability":[11],"to":[12,138],"disentangle":[13],"complex":[14],"data":[15,37],"structures.":[16],"Independent":[17],"vector":[18,79],"analysis":[19,80],"(IVA),":[20],"a":[21,71,83],"data-driven":[22],"approach,":[23],"simultaneously":[24],"extracts":[25],"global":[26],"spatial":[27],"and":[28,53,102],"temporal":[29],"patterns":[30],"from":[31],"multi-subject":[32],"functional":[33],"magnetic":[34],"resonance":[35],"imaging":[36],"while":[38],"preserving":[39],"individual":[40],"variability.":[41],"However,":[42],"performance":[44],"of":[45,51,109,122],"IVA":[46,115],"deteriorates":[47],"when":[48],"number":[50],"datasets":[52,63],"components":[54,61,101,134],"increases\u2014especially":[55],"scenarios":[57],"where":[58],"correlations":[59],"among":[60],"across":[62],"are":[64,135],"weak.":[65],"In":[66],"this":[67],"paper,":[68],"we":[69],"propose":[70],"novel":[72],"model:":[73],"non-orthogonal":[75],"adaptive":[76,94],"constrained":[77],"independent":[78],"integrated":[81],"with":[82],"multivariate":[84],"generalized":[85],"Gaussian":[86],"mixture":[87],"model":[88,92],"(non-orthogonal":[89],"acIVAMGGMM).":[90],"This":[91],"introduces":[93],"control":[95],"over":[96],"relationship":[98],"between":[99],"estimated":[100],"reference":[103,111],"signals,":[104],"thereby":[105],"facilitating":[106],"integration":[108],"multiple":[110],"signals":[112],"into":[113],"framework.":[116],"Experimental":[117],"results":[118],"highlight":[119],"effectiveness":[121],"proposed":[124],"method,":[125],"showing":[126],"sub-stantial":[127],"improvements":[128],"component":[130],"separation.":[131],"The":[132],"extracted":[133],"further":[136],"utilized":[137],"identify":[139],"brain":[140],"networks":[141],"impacted":[142],"by":[143],"Schizophrenia.":[144]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-28T00:00:00"}
