{"id":"https://openalex.org/W4406322195","doi":"https://doi.org/10.1109/access.2025.3529179","title":"End-to-End Stroke Imaging Analysis Using Effective Connectivity and Interpretable Artificial Intelligence","display_name":"End-to-End Stroke Imaging Analysis Using Effective Connectivity and Interpretable Artificial Intelligence","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4406322195","doi":"https://doi.org/10.1109/access.2025.3529179"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3529179","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3529179","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3529179","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076278742","display_name":"Wojciech Ci\u0119\u017cobka","orcid":"https://orcid.org/0000-0003-2972-710X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wojciech Ciezobka","raw_affiliation_strings":["Sano Centre for Computational Medicine, Krak&#x00F3;w, Poland","Sano Centre for Computational Medicine, Czarnowiejska 36 building C5, Krak&#x00F3;w, Poland"],"raw_orcid":"https://orcid.org/0000-0003-2972-710X","affiliations":[{"raw_affiliation_string":"Sano Centre for Computational Medicine, Krak&#x00F3;w, Poland","institution_ids":[]},{"raw_affiliation_string":"Sano Centre for Computational Medicine, Czarnowiejska 36 building C5, Krak&#x00F3;w, Poland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008777505","display_name":"Joan Falc\u00f3-Roget","orcid":"https://orcid.org/0000-0002-9410-6361"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joan Falc\u00f3-Roget","raw_affiliation_strings":["Sano Centre for Computational Medicine, Krak&#x00F3;w, Poland","Sano Centre for Computational Medicine, Czarnowiejska 36 building C5, Krak&#x00F3;w, Poland"],"raw_orcid":"https://orcid.org/0000-0002-9410-6361","affiliations":[{"raw_affiliation_string":"Sano Centre for Computational Medicine, Krak&#x00F3;w, Poland","institution_ids":[]},{"raw_affiliation_string":"Sano Centre for Computational Medicine, Czarnowiejska 36 building C5, Krak&#x00F3;w, Poland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013891438","display_name":"Cemal Koba","orcid":"https://orcid.org/0000-0001-7097-1441"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cemal Koba","raw_affiliation_strings":["Sano Centre for Computational Medicine, Krak&#x00F3;w, Poland","Sano Centre for Computational Medicine, Czarnowiejska 36 building C5, Krak&#x00F3;w, Poland"],"raw_orcid":"https://orcid.org/0000-0001-7097-1441","affiliations":[{"raw_affiliation_string":"Sano Centre for Computational Medicine, Krak&#x00F3;w, Poland","institution_ids":[]},{"raw_affiliation_string":"Sano Centre for Computational Medicine, Czarnowiejska 36 building C5, Krak&#x00F3;w, Poland","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047749964","display_name":"Alessandro Crimi","orcid":"https://orcid.org/0000-0001-5397-6363"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alessandro Crimi","raw_affiliation_strings":["Sano Centre for Computational Medicine, Krak&#x00F3;w, Poland","Sano Centre for Computational Medicine, Czarnowiejska 36 building C5, Krak&#x00F3;w, Poland"],"raw_orcid":"https://orcid.org/0000-0001-5397-6363","affiliations":[{"raw_affiliation_string":"Sano Centre for Computational Medicine, Krak&#x00F3;w, Poland","institution_ids":[]},{"raw_affiliation_string":"Sano Centre for Computational Medicine, Czarnowiejska 36 building C5, Krak&#x00F3;w, Poland","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.2984,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.87050419,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"13","issue":null,"first_page":"10227","last_page":"10239"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.909600019454956,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.909600019454956,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6536455154418945},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6055644154548645},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.5883064866065979},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42508402466773987},{"id":"https://openalex.org/keywords/stroke","display_name":"Stroke (engine)","score":0.4149734079837799},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34781375527381897},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11212345957756042}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6536455154418945},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6055644154548645},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.5883064866065979},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42508402466773987},{"id":"https://openalex.org/C2780645631","wikidata":"https://www.wikidata.org/wiki/Q671554","display_name":"Stroke (engine)","level":2,"score":0.4149734079837799},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34781375527381897},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11212345957756042},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3529179","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3529179","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:aa69c86ca86f421680368d041e07b9c7","is_oa":true,"landing_page_url":"https://doaj.org/article/aa69c86ca86f421680368d041e07b9c7","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":"IEEE Access, Vol 13, Pp 10227-10239 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3529179","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3529179","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W793431435","https://openalex.org/W1010359952","https://openalex.org/W1560724230","https://openalex.org/W1752598806","https://openalex.org/W1964127964","https://openalex.org/W1971421925","https://openalex.org/W1988812422","https://openalex.org/W1989312953","https://openalex.org/W2041782669","https://openalex.org/W2047673811","https://openalex.org/W2051239559","https://openalex.org/W2066346175","https://openalex.org/W2083278075","https://openalex.org/W2085009317","https://openalex.org/W2103179919","https://openalex.org/W2113762408","https://openalex.org/W2117663940","https://openalex.org/W2138905229","https://openalex.org/W2142858796","https://openalex.org/W2153857579","https://openalex.org/W2158054309","https://openalex.org/W2167822639","https://openalex.org/W2216543600","https://openalex.org/W2298354499","https://openalex.org/W2465207860","https://openalex.org/W2516809705","https://openalex.org/W2536956629","https://openalex.org/W2558748708","https://openalex.org/W2664915385","https://openalex.org/W2760921629","https://openalex.org/W2768991694","https://openalex.org/W2769180770","https://openalex.org/W2781772938","https://openalex.org/W2782312356","https://openalex.org/W2902923903","https://openalex.org/W2951583631","https://openalex.org/W2951617899","https://openalex.org/W2952719324","https://openalex.org/W2980286315","https://openalex.org/W3033702084","https://openalex.org/W3042526937","https://openalex.org/W3091792199","https://openalex.org/W3094131054","https://openalex.org/W3152893301","https://openalex.org/W3176686676","https://openalex.org/W3179250235","https://openalex.org/W3199240627","https://openalex.org/W3205096573","https://openalex.org/W3207745421","https://openalex.org/W3211247205","https://openalex.org/W4224903266","https://openalex.org/W4231726431","https://openalex.org/W4283773174","https://openalex.org/W4295605475","https://openalex.org/W4319762935","https://openalex.org/W4322627332","https://openalex.org/W4322707072","https://openalex.org/W4372325194","https://openalex.org/W4380202799","https://openalex.org/W4382565041","https://openalex.org/W4386716628","https://openalex.org/W4392112055","https://openalex.org/W4392636949","https://openalex.org/W4400513689","https://openalex.org/W4401059441","https://openalex.org/W4404007098","https://openalex.org/W4407866160","https://openalex.org/W6755821303","https://openalex.org/W6796184174"],"related_works":["https://openalex.org/W2151749779","https://openalex.org/W3179968364","https://openalex.org/W1999612375","https://openalex.org/W2938107654","https://openalex.org/W3196421258","https://openalex.org/W4387301579","https://openalex.org/W2763956190","https://openalex.org/W3008587939","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"In":[0],"this":[1,16,36,147],"paper,":[2],"we":[3,124,150],"propose":[4],"a":[5,41,55,102,187,219,257,264,413],"reservoir":[6,193,396,449],"computing-based":[7,194],"and":[8,46,76,79,88,98,111,208,252,272,316,360,401,417,440],"directed":[9,42,168,283,403,414],"graph":[10,43,169,181,239,305,404,415,452],"analysis":[11,191,419],"pipeline.":[12,154],"The":[13,238],"goal":[14],"of":[15,59,70,74,113,128,138,163,229,232,281,301,336,395,420,438],"pipeline":[17,156,216,262,391],"is":[18,38,68,196,242,277],"to":[19,198,222,245,295,331,352,398,434],"define":[20,399],"an":[21,152,296,334],"efficient":[22],"brain":[23,118,136,230,341,429,442],"representation":[24,37],"for":[25,85,105,267,380],"connectivity":[26,162,202,226,349],"in":[27,116,289,376,408,412,428],"stroke":[28,61,139,270,353,439],"data":[29],"derived":[30],"from":[31],"magnetic":[32],"resonance":[33],"imaging.":[34],"Ultimately,":[35],"used":[39,411],"within":[40,64],"convolutional":[44,182,240,306,453],"architecture":[45,241],"investigated":[47,177],"with":[48,94,158,192,323,431],"explainable":[49,332,418,447],"artificial":[50],"intelligence":[51],"(AI)":[52],"tools,":[53,333],"offering":[54],"more":[56],"detailed":[57],"understanding":[58,437],"how":[60],"alters":[62],"communication":[63],"the":[65,71,109,117,126,135,143,160,164,190,215,224,261,275,279,292,299,324,340,347,393,432],"brain.":[66,165],"Stroke":[67],"one":[69,204,209],"leading":[72],"causes":[73],"mortality":[75],"morbidity":[77],"worldwide,":[78],"it":[80],"demands":[81],"precise":[82],"diagnostic":[83],"tools":[84],"timely":[86],"intervention":[87],"improved":[89],"patient":[90],"outcomes.":[91],"Neuroimaging":[92],"data,":[93],"their":[95],"rich":[96],"structural":[97],"functional":[99],"information,":[100],"provide":[101],"fertile":[103],"ground":[104],"biomarker":[106],"discovery.":[107],"However,":[108],"complexity":[110],"variability":[112],"information":[114],"flow":[115],"require":[119],"advanced":[120],"analysis,":[121],"especially":[122],"if":[123],"consider":[125],"case":[127],"disrupted":[129,337],"networks":[130,231,338,342],"as":[131,249],"those":[132],"given":[133,145,325],"by":[134,146,180,303,309,318],"connectome":[137],"patients.":[140],"To":[141,185],"address":[142],"needs":[144],"complex":[148],"scenario":[149],"proposed":[151,388],"end-to-end":[153],"This":[155,166,345,363,423],"begins":[157],"defining":[159],"effective":[161,201,225,348],"allows":[167],"network":[170,183],"representations":[171],"that":[172],"have":[173,186],"not":[174,367],"been":[175],"fully":[176],"so":[178],"far":[179],"classifiers.":[184],"complete":[188,258],"overview,":[189],"causality":[195,400],"compared":[197,244],"other":[199,441],"two":[200],"approaches:":[203],"linear":[205],"(Granger":[206],"causality)":[207],"non-linear":[210],"method":[211,424],"(transfer":[212],"entropy).":[213],"Then,":[214],"subsequently":[217],"incorporates":[218],"classification":[220,265,293],"module":[221,266],"categorize":[223],"(directed":[227],"graphs)":[228],"patients":[233,271],"versus":[234],"matched":[235],"healthy":[236,273],"control.":[237],"also":[243,373],"legacy":[246],"methods":[247],"such":[248],"random":[250,314],"forest":[251],"support":[253,320],"vector":[254,321],"machine":[255,322,389],"providing":[256],"benchmark.":[259],"While":[260],"includes":[263],"distinguishing":[268],"between":[269],"controls,":[274],"focus":[276],"on":[278],"interpretation":[280,335],"these":[282],"graphs,":[284],"which":[285,406],"reveal":[286],"critical":[287],"disruptions":[288],"connectivity.":[290],"Indeed,":[291],"led":[294],"area":[297],"under":[298],"curve":[300],"0.69":[302],"using":[304,310,319],"networks,":[307,405,430,454],"0.72":[308],"local":[311],"topological":[312],"profiling":[313],"forest,":[315],"0.71":[317],"heterogeneous":[326],"dataset.":[327],"More":[328],"importantly,":[329],"thanks":[330],"across":[339],"was":[343],"possible.":[344],"elucidates":[346],"biomarker\u2019s":[350],"contribution":[351],"classification,":[354],"fostering":[355],"insights":[356],"into":[357,384],"disease":[358],"mechanisms":[359],"treatment":[361],"responses.":[362],"transparent":[364],"analytical":[365],"framework":[366],"only":[368],"enhances":[369],"clinical":[370,385],"interpretability":[371],"but":[372],"instills":[374],"confidence":[375],"decision-making":[377],"processes,":[378],"crucial":[379],"translating":[381],"research":[382],"findings":[383],"practice.":[386],"Our":[387],"learning":[390],"showcases":[392],"potential":[394,433],"computing":[397],"therefore":[402],"can":[407],"turn":[409],"be":[410],"classifier":[416],"neuroimaging":[421],"data.":[422],"prioritizes":[425],"uncovering":[426],"miscommunication":[427],"improve":[435],"our":[436],"diseases.INDEX":[443],"TERMS":[444],"Effective":[445],"connectivity,":[446],"AI,":[448],"computing,":[450],"stroke,":[451],"GCN,":[455],"GNN.":[456]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-06-20T22:02:38.213706","created_date":"2025-01-14T00:00:00"}
