{"id":"https://openalex.org/W7139043077","doi":"https://doi.org/10.48550/arxiv.2603.17304","title":"3D MRI-Based Alzheimer's Disease Classification Using Multi-Modal 3D CNN with Leakage-Aware Subject-Level Evaluation","display_name":"3D MRI-Based Alzheimer's Disease Classification Using Multi-Modal 3D CNN with Leakage-Aware Subject-Level Evaluation","publication_year":2026,"publication_date":"2026-03-18","ids":{"openalex":"https://openalex.org/W7139043077","doi":"https://doi.org/10.48550/arxiv.2603.17304"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.17304","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17304","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.17304","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130199472","display_name":"Md Sifat","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sifat, Md","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029139078","display_name":"Sania Akter","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Akter, Sania","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063245603","display_name":"Akif Islam","orcid":"https://orcid.org/0009-0004-2755-7316"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Islam, Akif","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008769867","display_name":"Md. Ekramul Hamid","orcid":"https://orcid.org/0000-0001-8029-013X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hamid, Md. Ekramul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130033025","display_name":"Abu Saleh Musa Miah","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Miah, Abu Saleh Musa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034943687","display_name":"Najmul Hassan","orcid":"https://orcid.org/0000-0001-6346-7669"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hassan, Najmul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072523228","display_name":"Md Abdur Rahim","orcid":"https://orcid.org/0000-0003-2300-1420"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rahim, Md Abdur","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129931147","display_name":"Jungpil Shin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shin, Jungpil","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10009","display_name":"Dementia and Cognitive Impairment Research","score":0.5324000120162964,"subfield":{"id":"https://openalex.org/subfields/2738","display_name":"Psychiatry and Mental health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10009","display_name":"Dementia and Cognitive Impairment Research","score":0.5324000120162964,"subfield":{"id":"https://openalex.org/subfields/2738","display_name":"Psychiatry and Mental health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.1290999948978424,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.06069999933242798,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6482999920845032},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5690000057220459},{"id":"https://openalex.org/keywords/neuroimaging","display_name":"Neuroimaging","score":0.5523999929428101},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5386000275611877},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.47749999165534973},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.40470001101493835},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.3880000114440918},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.3677000105381012}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7174999713897705},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6783000230789185},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6482999920845032},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5690000057220459},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.5523999929428101},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5386000275611877},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.47749999165534973},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.40470001101493835},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3880000114440918},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3677000105381012},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3553999960422516},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3544999957084656},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3285999894142151},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.31790000200271606},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.3093999922275543},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.28200000524520874},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C2779370443","wikidata":"https://www.wikidata.org/wiki/Q1776627","display_name":"Surgical planning","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C2778373026","wikidata":"https://www.wikidata.org/wiki/Q4738819","display_name":"Alzheimer's Disease Neuroimaging Initiative","level":4,"score":0.2522999942302704},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.17304","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17304","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.17304","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17304","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.46300792694091797}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"learning":[1],"has":[2],"become":[3],"an":[4],"important":[5],"tool":[6],"for":[7,73,219,244],"Alzheimer's":[8,176,245],"disease":[9,58,246],"(AD)":[10],"classification":[11,75],"from":[12,23],"structural":[13,85,178],"MRI.":[14],"Many":[15],"existing":[16],"studies":[17],"analyze":[18],"individual":[19],"2D":[20],"slices":[21],"extracted":[22],"MRI":[24,80,242],"volumes,":[25],"while":[26],"clinical":[27],"neuroimaging":[28],"practice":[29],"typically":[30],"relies":[31],"on":[32,115,157,198],"the":[33,39,116,154,162,204,220,224,237],"full":[34],"three":[35],"dimensional":[36],"structure":[37],"of":[38,133,143,203,240],"brain.":[40],"From":[41],"this":[42,62,64],"perspective,":[43],"volumetric":[44,221,241],"analysis":[45,243],"may":[46,189],"better":[47,181],"capture":[48,106],"spatial":[49],"relationships":[50],"among":[51],"brain":[52],"regions":[53],"that":[54,153,169],"are":[55,170],"relevant":[56],"to":[57,105,172],"progression.":[59],"Motivated":[60],"by":[61],"idea,":[63],"work":[65],"proposes":[66],"a":[67,130,140,199,230],"multimodal":[68,226],"3D":[69,227],"convolutional":[70],"neural":[71],"network":[72],"AD":[74],"using":[76,122],"raw":[77],"OASIS":[78,119],"1":[79,120],"volumes.":[81],"The":[82,110],"model":[83,155],"combines":[84],"T1":[86],"information":[87],"with":[88,175],"gray":[89],"matter,":[90,92],"white":[91],"and":[93,139,166,186,210,235],"cerebrospinal":[94],"fluid":[95],"probability":[96],"maps":[97],"obtained":[98],"through":[99],"FSL":[100],"FAST":[101],"segmentation":[102],"in":[103],"order":[104],"complementary":[107],"neuroanatomical":[108],"information.":[109],"proposed":[111,225],"approach":[112],"is":[113],"evaluated":[114],"clinically":[117],"labelled":[118],"cohort":[121],"5":[123],"fold":[124],"subject":[125,211,232],"level":[126,209,212,233],"cross":[127],"validation,":[128],"achieving":[129],"mean":[131],"accuracy":[132],"72.34%":[134],"plus":[135,145],"or":[136,146],"minus":[137,147],"4.66%":[138],"ROC":[141],"AUC":[142],"0.7781":[144],"0.0365.":[148],"GradCAM":[149],"visualizations":[150],"further":[151],"indicate":[152],"focuses":[156],"anatomically":[158],"meaningful":[159],"regions,":[160],"including":[161],"medial":[163],"temporal":[164],"lobe":[165],"ventricular":[167],"areas":[168],"known":[171],"be":[173],"associated":[174],"related":[177],"changes.":[179],"To":[180],"understand":[182],"how":[183],"data":[184],"representation":[185],"evaluation":[187],"strategies":[188],"influence":[190],"reported":[191],"performance,":[192],"additional":[193],"diagnostic":[194],"experiments":[195],"were":[196],"conducted":[197],"slice":[200,208],"based":[201],"version":[202],"dataset":[205],"under":[206],"both":[207],"protocols.":[213],"These":[214],"observations":[215],"help":[216],"provide":[217],"context":[218],"results.":[222],"Overall,":[223],"framework":[228],"establishes":[229],"reproducible":[231],"benchmark":[234],"highlights":[236],"potential":[238],"benefits":[239],"classification.":[247]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-20T00:00:00"}
