{"id":"https://openalex.org/W7204488714","doi":"https://doi.org/10.1109/peccii70991.2026.11661895","title":"DeepStrokeGuard: Explainable and Deployable Deep Learning for Brain Stroke Detection with Class Imbalance Handling","display_name":"DeepStrokeGuard: Explainable and Deployable Deep Learning for Brain Stroke Detection with Class Imbalance Handling","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7204488714","doi":"https://doi.org/10.1109/peccii70991.2026.11661895"},"language":"en","primary_location":{"id":"doi:10.1109/peccii70991.2026.11661895","doi":"https://doi.org/10.1109/peccii70991.2026.11661895","is_oa":true,"landing_page_url":"https://doi.org/10.1109/peccii70991.2026.11661895","pdf_url":null,"source":{"id":"https://openalex.org/S7407096946","display_name":"International Conference on Power, Electronics, Communications, Computing, and Intelligent Infrastructure (PECCII)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Power, Electronics, Communications, Computing, and Intelligent Infrastructure (PECCII)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/peccii70991.2026.11661895","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5148467738","display_name":"Sayed Al Mahmud","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I200606013","display_name":"Daffodil International University","ror":"https://ror.org/052t4a858","country_code":"BD","type":"education","lineage":["https://openalex.org/I200606013"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Sayed Al Mahmud","raw_affiliation_strings":["Daffodil International University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Daffodil International University","institution_ids":["https://openalex.org/I200606013"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139174946","display_name":"Md. Siam Ahmed","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I200606013","display_name":"Daffodil International University","ror":"https://ror.org/052t4a858","country_code":"BD","type":"education","lineage":["https://openalex.org/I200606013"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Md. Siam Ahmed","raw_affiliation_strings":["Daffodil International University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Daffodil International University","institution_ids":["https://openalex.org/I200606013"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129580176","display_name":"Md. Ferdous Jaman","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I200606013","display_name":"Daffodil International University","ror":"https://ror.org/052t4a858","country_code":"BD","type":"education","lineage":["https://openalex.org/I200606013"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Md. Ferdous Jaman","raw_affiliation_strings":["Daffodil International University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Daffodil International University","institution_ids":["https://openalex.org/I200606013"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022184940","display_name":"Md. Ashikur Rahaman","orcid":"https://orcid.org/0009-0002-6831-1377","observed_orcids":["https://orcid.org/0009-0002-6831-1377"]},"institutions":[{"id":"https://openalex.org/I200606013","display_name":"Daffodil International University","ror":"https://ror.org/052t4a858","country_code":"BD","type":"education","lineage":["https://openalex.org/I200606013"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Md. Ashikur Rahaman","raw_affiliation_strings":["Daffodil International University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Daffodil International University","institution_ids":["https://openalex.org/I200606013"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109681089","display_name":"Md Mobinul Islam","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I200606013","display_name":"Daffodil International University","ror":"https://ror.org/052t4a858","country_code":"BD","type":"education","lineage":["https://openalex.org/I200606013"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Md Mobinul Islam","raw_affiliation_strings":["Daffodil International University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Daffodil International University","institution_ids":["https://openalex.org/I200606013"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5148467397","display_name":"Sk Fahim Sadik","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I200606013","display_name":"Daffodil International University","ror":"https://ror.org/052t4a858","country_code":"BD","type":"education","lineage":["https://openalex.org/I200606013"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Sk Fahim Sadik","raw_affiliation_strings":["Daffodil International University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Daffodil International University","institution_ids":["https://openalex.org/I200606013"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I200606013"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.59793865,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.38350000977516174,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.38350000977516174,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.17409999668598175,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10227","display_name":"Acute Ischemic Stroke Management","score":0.14949999749660492,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Clinical Neurology"},"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/stroke-detection","display_name":"stroke detection","score":0.9990000128746033},{"id":"https://openalex.org/keywords/computed-tomography","display_name":"computed tomography","score":0.5619999766349792},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.9950000047683716},{"id":"https://openalex.org/keywords/explainable-deep-learning","display_name":"explainable deep learning","score":0.8799999952316284},{"id":"https://openalex.org/keywords/grad-cam","display_name":"Grad-CAM","score":0.984000027179718},{"id":"https://openalex.org/keywords/lime","display_name":"lime","score":1.0},{"id":"https://openalex.org/keywords/threshold-adjustment","display_name":"threshold adjustment","score":0.7170000076293945},{"id":"https://openalex.org/keywords/youden-index","display_name":"Youden index","score":0.9800000190734863},{"id":"https://openalex.org/keywords/class-weights","display_name":"class weighting","score":0.7789999842643738},{"id":"https://openalex.org/keywords/data-augmentation","display_name":"data augmentation","score":0.9089999794960022},{"id":"https://openalex.org/keywords/densenet-121","display_name":"DenseNet121","score":0.871999979019165},{"id":"https://openalex.org/keywords/resnet-50","display_name":"ResNet50","score":0.9980000257492065},{"id":"https://openalex.org/keywords/xception","display_name":"Xception","score":0.8090000152587891},{"id":"https://openalex.org/keywords/lightweight-models","display_name":"lightweight models","score":0.5889999866485596},{"id":"https://openalex.org/keywords/false-negative-reduction","display_name":"false negative reduction","score":0.746999979019165}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6618000268936157},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6582000255584717},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5396000146865845},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5249999761581421},{"id":"https://openalex.org/C2780645631","wikidata":"https://www.wikidata.org/wiki/Q671554","display_name":"Stroke (engine)","level":2,"score":0.4374000132083893},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.32010000944137573},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3158000111579895},{"id":"https://openalex.org/C2778542668","wikidata":"https://www.wikidata.org/wiki/Q618076","display_name":"Deep brain stimulation","level":4,"score":0.28600001335144043},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.28209999203681946},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.2574000060558319},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2574000060558319}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/peccii70991.2026.11661895","doi":"https://doi.org/10.1109/peccii70991.2026.11661895","is_oa":true,"landing_page_url":"https://doi.org/10.1109/peccii70991.2026.11661895","pdf_url":null,"source":{"id":"https://openalex.org/S7407096946","display_name":"International Conference on Power, Electronics, Communications, Computing, and Intelligent Infrastructure (PECCII)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Power, Electronics, Communications, Computing, and Intelligent Infrastructure (PECCII)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/peccii70991.2026.11661895","doi":"https://doi.org/10.1109/peccii70991.2026.11661895","is_oa":true,"landing_page_url":"https://doi.org/10.1109/peccii70991.2026.11661895","pdf_url":null,"source":{"id":"https://openalex.org/S7407096946","display_name":"International Conference on Power, Electronics, Communications, Computing, and Intelligent Infrastructure (PECCII)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Power, Electronics, Communications, Computing, and Intelligent Infrastructure (PECCII)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8048999905586243,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W4400641340","https://openalex.org/W4403913069","https://openalex.org/W4406690233","https://openalex.org/W4407054842","https://openalex.org/W4409763801","https://openalex.org/W4410131180","https://openalex.org/W4412815012","https://openalex.org/W4414610393","https://openalex.org/W4415763710","https://openalex.org/W7108224515","https://openalex.org/W7130505791"],"related_works":["https://openalex.org/W7215734961","https://openalex.org/W7204446627","https://openalex.org/W6922599953","https://openalex.org/W7213458371","https://openalex.org/W7117727864","https://openalex.org/W7213285070","https://openalex.org/W4415718354","https://openalex.org/W7167089648","https://openalex.org/W7204435035","https://openalex.org/W4415763710"],"abstract_inverted_index":{"Detection":[0],"of":[1,84,87,90,93,97,103,132,135,145,180],"brain":[2,105,183],"strokes":[3],"using":[4,72],"CT":[5,157],"scan":[6],"is":[7,41],"still":[8],"a":[9,81,100,114],"difficult":[10],"task":[11],"because":[12],"the":[13,23,32,133,136,146,164,178],"class":[14,108],"imbalances":[15],"in":[16,43],"normal":[17],"and":[18,31,54,56,69,95,110,126,138,162,172],"stroke":[19],"rates":[20,26],"are":[21,27],"high,":[22],"false":[24],"negative":[25],"also":[28],"very":[29,170],"high":[30],"models":[33,51],"lack":[34],"interpretability.":[35],"A":[36,152],"full":[37],"framework":[38,154,166],"called":[39],"DeepStrokeGuard":[40],"presented":[42],"this":[44],"paper":[45],"that":[46],"reviews":[47],"various":[48],"deep":[49],"learning":[50],"(DenseNet121,":[52],"ResNet50":[53,78],"Xception)":[55],"solves":[57],"these":[58],"issues":[59],"by":[60],"applying":[61],"systematic":[62],"preprocessing,":[63],"data":[64],"augmentation,":[65],"dynamically":[66],"weighted":[67,109],"classes,":[68],"threshold":[70,111],"tuning":[71],"Youden\u2019s":[73],"J":[74],"statistic.":[75],"The":[76],"fine-tuned":[77],"has":[79],"achieved":[80],"test":[82,101],"accuracy":[83,147],"99.77%,":[85],"F1-score":[86],"1.00,":[88,91],"AUC":[89],"precision":[92],"99.5%,":[94],"recall":[96],"100%":[98],"on":[99],"set":[102],"2515":[104],"CTs.":[106],"DenseNet121":[107],"tuned":[112],"offers":[113],"lightweight":[115],"alternative":[116],"at":[117],"97.25%":[118],"with":[119,159],"6.96M":[120],"parameters":[121],"only.":[122],"We":[123],"combine":[124],"Grad-CAM":[125],"LIME":[127],"to":[128,150],"offer":[129],"visual/pixel":[130],"evaluation":[131],"extensions":[134],"stroke,":[137],"our":[139],"ablation":[140],"experiment":[141],"discloses":[142],"an":[143,181],"enhancement":[144],"between":[148],"68\u201378%":[149],"99.77%.":[151],"web-based":[153],"facilitates":[155],"real-time":[156],"analysis":[158],"confidence":[160],"scores":[161],"thus,":[163],"suggested":[165],"can":[167],"be":[168],"both":[169],"accurate":[171],"practically":[173],"applicable":[174],"as":[175],"grounded":[176],"towards":[177],"detection":[179],"early":[182],"stroke.":[184]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-08-28T00:00:00"}
