{"id":"https://openalex.org/W4401252803","doi":"https://doi.org/10.3233/idt-240652","title":"Enhancing alzheimer\u2019s diagnosis through optimized brain lesion classification in MRI with attention-driven grid feature fusion","display_name":"Enhancing alzheimer\u2019s diagnosis through optimized brain lesion classification in MRI with attention-driven grid feature fusion","publication_year":2024,"publication_date":"2024-08-02","ids":{"openalex":"https://openalex.org/W4401252803","doi":"https://doi.org/10.3233/idt-240652"},"language":"en","primary_location":{"id":"doi:10.3233/idt-240652","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-240652","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Decision Technologies","raw_type":"journal-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/A5111278558","display_name":"Manas Ranjan Mohanty","orcid":null},"institutions":[{"id":"https://openalex.org/I67357951","display_name":"KIIT University","ror":"https://ror.org/00k8zt527","country_code":"IN","type":"education","lineage":["https://openalex.org/I67357951"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manas Ranjan Mohanty","raw_affiliation_strings":["School of Computer Engineering, KIIT Deemed to be University, Odisha, India"],"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, KIIT Deemed to be University, Odisha, India","institution_ids":["https://openalex.org/I67357951"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029805698","display_name":"Pradeep Kumar Mallick","orcid":"https://orcid.org/0000-0002-1207-0757"},"institutions":[{"id":"https://openalex.org/I67357951","display_name":"KIIT University","ror":"https://ror.org/00k8zt527","country_code":"IN","type":"education","lineage":["https://openalex.org/I67357951"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Pradeep Kumar Mallick","raw_affiliation_strings":["School of Computer Engineering, KIIT Deemed to be University, Odisha, India"],"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, KIIT Deemed to be University, Odisha, India","institution_ids":["https://openalex.org/I67357951"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106253790","display_name":"Rajesh Kedarnath Navandar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rajesh Kedarnath Navandar","raw_affiliation_strings":["Department of Electronic and Telecommunication Engineering, JSPM Jayawantrao Sawant College of Engineering Hadaspar, Pune, India"],"affiliations":[{"raw_affiliation_string":"Department of Electronic and Telecommunication Engineering, JSPM Jayawantrao Sawant College of Engineering Hadaspar, Pune, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057714218","display_name":"Gyoo\u2010Soo Chae","orcid":"https://orcid.org/0000-0002-4592-8895"},"institutions":[{"id":"https://openalex.org/I35919505","display_name":"Baekseok University","ror":"https://ror.org/045qyjz25","country_code":"KR","type":"education","lineage":["https://openalex.org/I35919505"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gyoo-Soo Chae","raw_affiliation_strings":["Division of Advanced IT, Baekseok University, Korea"],"affiliations":[{"raw_affiliation_string":"Division of Advanced IT, Baekseok University, Korea","institution_ids":["https://openalex.org/I35919505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071195676","display_name":"Alok Kumar Jagadev","orcid":null},"institutions":[{"id":"https://openalex.org/I67357951","display_name":"KIIT University","ror":"https://ror.org/00k8zt527","country_code":"IN","type":"education","lineage":["https://openalex.org/I67357951"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Alok Kumar Jagadev","raw_affiliation_strings":["School of Computer Engineering, KIIT Deemed to be University, Odisha, India"],"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, KIIT Deemed to be University, Odisha, India","institution_ids":["https://openalex.org/I67357951"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5029805698"],"corresponding_institution_ids":["https://openalex.org/I67357951"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1322314,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"3","first_page":"1993","last_page":"2018"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9994000196456909,"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":0.9994000196456909,"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"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9901000261306763,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9670000076293945,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6159892082214355},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5315489768981934},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5283031463623047},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5122169852256775},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48905453085899353},{"id":"https://openalex.org/keywords/lesion","display_name":"Lesion","score":0.4816388189792633},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.4243295192718506},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3129209280014038},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.1368492841720581},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07324555516242981}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6159892082214355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5315489768981934},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5283031463623047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5122169852256775},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48905453085899353},{"id":"https://openalex.org/C2781156865","wikidata":"https://www.wikidata.org/wiki/Q827023","display_name":"Lesion","level":2,"score":0.4816388189792633},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4243295192718506},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3129209280014038},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.1368492841720581},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07324555516242981},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/idt-240652","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-240652","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Decision Technologies","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5899999737739563,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W2560576162","https://openalex.org/W2912541111","https://openalex.org/W2981030558","https://openalex.org/W2987281556","https://openalex.org/W3028368226","https://openalex.org/W3045776219","https://openalex.org/W3097287327","https://openalex.org/W3115069763","https://openalex.org/W3169552844","https://openalex.org/W3208463329","https://openalex.org/W4206730042","https://openalex.org/W4224040930","https://openalex.org/W4224261758","https://openalex.org/W4224306105","https://openalex.org/W4225531241","https://openalex.org/W4281730963","https://openalex.org/W4282961647","https://openalex.org/W4286254503","https://openalex.org/W4288969537","https://openalex.org/W4290694458","https://openalex.org/W4293581659","https://openalex.org/W4302028668","https://openalex.org/W4304998080","https://openalex.org/W4308946426","https://openalex.org/W4311423536","https://openalex.org/W4315574499","https://openalex.org/W4318570647","https://openalex.org/W4320521693","https://openalex.org/W4321457716","https://openalex.org/W4323923911","https://openalex.org/W4324316188","https://openalex.org/W4360864999","https://openalex.org/W4363675552","https://openalex.org/W4364378262","https://openalex.org/W4379185441","https://openalex.org/W4381384569","https://openalex.org/W4381432381","https://openalex.org/W4382678343","https://openalex.org/W4382879258","https://openalex.org/W6770088937","https://openalex.org/W6809870058","https://openalex.org/W6846216052"],"related_works":["https://openalex.org/W2070328444","https://openalex.org/W2377161363","https://openalex.org/W3106127189","https://openalex.org/W2394514052","https://openalex.org/W2001448689","https://openalex.org/W2038281889","https://openalex.org/W2024750207","https://openalex.org/W2030498840","https://openalex.org/W4396792513","https://openalex.org/W4386159726"],"abstract_inverted_index":{"This":[0,142],"paper":[1],"explores":[2],"cognitive":[3],"interface":[4],"technology,":[5],"aiming":[6],"to":[7,40,120,235],"tackle":[8],"current":[9],"challenges":[10,42],"and":[11,33,55,89,150,182,199,246,262,268,285,295,326],"shed":[12],"light":[13],"on":[14,30,110],"the":[15,50,74,95,111,122,135,146,154,166,190,209,212,223,228,237,240,276,299,313,318],"prospects":[16],"of":[17,26,53,57,132,178,211,227,239,283,298],"brain-computer":[18],"interfaces":[19],"(BCIs).":[20],"It":[21,62],"provides":[22],"a":[23,139],"comprehensive":[24],"examination":[25],"their":[27,244],"transformative":[28],"impact":[29],"medical":[31],"technology":[32],"patient":[34],"well-being.":[35],"Specifically,":[36],"this":[37],"study":[38],"contributes":[39],"addressing":[41],"in":[43,134,176,216,281,309],"classifying":[44],"brain":[45],"lesion":[46,218],"images":[47],"arising":[48],"from":[49,85],"complex":[51],"nature":[52],"lesions":[54],"limitations":[56],"traditional":[58],"deep":[59,70],"learning":[60,71,203],"approaches.":[61],"introduces":[63],"advanced":[64],"feature":[65,98,156,168,186,213,323],"fusion":[66,92,99,169,187,214,324],"models":[67,81,175],"that":[68,165],"leverage":[69],"algorithms,":[72],"including":[73,94],"African":[75],"vulture":[76],"optimization":[77,327],"(AVO)":[78],"algorithm.":[79],"These":[80],"integrate":[82],"informative":[83],"features":[84],"multiple":[86],"pre-trained":[87,174],"networks":[88],"employ":[90],"innovative":[91],"techniques,":[93],"attention-driven":[96],"grid":[97],"(ADGFF)":[100],"model.":[101],"The":[102,117,184,202,251,271,302],"ADGFF":[103],"model":[104,253,273,315],"incorporates":[105],"an":[106],"attention":[107],"mechanism":[108],"based":[109],"optimized":[112,185,254],"weights":[113],"obtained":[114],"using":[115],"AVO.":[116],"objective":[118],"is":[119,233],"improve":[121],"overall":[123],"accuracy":[124,284],"by":[125],"providing":[126],"fine-grained":[127],"control":[128],"over":[129],"different":[130,322],"regions":[131],"interest":[133],"input":[136],"image":[137,147],"through":[138],"grid-based":[140,143],"technique.":[141],"technique":[144,280],"divides":[145],"into":[148],"vertical":[149],"horizontal":[151],"grids,":[152],"simplifying":[153],"exemplar":[155],"generation":[157],"process":[158],"without":[159],"compromising":[160],"performance.":[161],"Experimental":[162],"results":[163],"demonstrate":[164],"proposed":[167,241,300],"strategies":[170,215,325],"consistently":[171,257],"outperform":[172],"individual":[173],"terms":[177,282],"accuracy,":[179,245,260],"sensitivity,":[180,261],"specificity,":[181],"F1-score.":[183],"strategies,":[188],"particularly":[189],"GRU-ADGFF":[191,252,272,314],"model,":[192],"further":[193],"enhance":[194],"classification":[195],"performance,":[196,311],"outperforming":[197],"CNN":[198],"RNN":[200],"classifiers.":[201],"progress":[204],"analysis":[205,291],"shows":[206],"convergence,":[207],"indicating":[208],"effectiveness":[210,267],"capturing":[217],"patterns.":[219],"AUC-ROC":[220],"curves":[221],"highlight":[222],"superior":[224],"discriminatory":[225],"capabilities":[226],"ADGFF-AVO":[229],"strategy.":[230],"Five-fold":[231],"cross-validation":[232],"employed":[234],"assess":[236],"performance":[238],"models,":[242],"demonstrating":[243,265],"few":[247],"other":[248],"accuracy-based":[249],"measures.":[250],"with":[255,312],"AVO":[256],"achieves":[258],"high":[259],"AUC":[263],"values,":[264],"its":[266],"generalization":[269],"capability.":[270],"also":[274],"outperforms":[275],"majority":[277],"voting":[278],"ensemble":[279],"discriminative":[286],"ability.":[287],"Additionally,":[288],"execution":[289],"time":[290],"reveals":[292],"good":[293],"scalability":[294],"resource":[296],"utilization":[297],"models.":[301],"Friedman":[303],"rank":[304],"test":[305],"confirms":[306],"significant":[307],"differences":[308],"classifier":[310],"emerging":[316],"as":[317],"top-performing":[319],"method":[320],"across":[321],"algorithms.":[328]},"counts_by_year":[],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}