{"id":"https://openalex.org/W7162648700","doi":"https://doi.org/10.48550/arxiv.2605.28397","title":"Adaptive Temporal Gating of Longitudinal Magnetic Resonance Imaging for Alzheimer's Prediction","display_name":"Adaptive Temporal Gating of Longitudinal Magnetic Resonance Imaging for Alzheimer's Prediction","publication_year":2026,"publication_date":"2026-05-27","ids":{"openalex":"https://openalex.org/W7162648700","doi":"https://doi.org/10.48550/arxiv.2605.28397"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.28397","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28397","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.28397","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037932192","display_name":"Alireza Moayedikia","orcid":"https://orcid.org/0000-0001-7229-3699"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Moayedikia, Alireza","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137293104","display_name":"Sara Fin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fin, Sara","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137281823","display_name":"Alicia Troncoso Lora","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lora, Alicia Troncoso","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137217560","display_name":"Uffe Kock Wiil","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wiil, Uffe Kock","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":0.7378000020980835,"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":0.7378000020980835,"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":0.15530000627040863,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.02850000001490116,"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/discriminative-model","display_name":"Discriminative model","score":0.8343999981880188},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7630000114440918},{"id":"https://openalex.org/keywords/gating","display_name":"Gating","score":0.7006999850273132},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5633999705314636},{"id":"https://openalex.org/keywords/neuroimaging","display_name":"Neuroimaging","score":0.5248000025749207},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.504800021648407},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.4650999903678894},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.44909998774528503},{"id":"https://openalex.org/keywords/functional-magnetic-resonance-imaging","display_name":"Functional magnetic resonance imaging","score":0.4417000114917755}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8343999981880188},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7630000114440918},{"id":"https://openalex.org/C194544171","wikidata":"https://www.wikidata.org/wiki/Q21105679","display_name":"Gating","level":2,"score":0.7006999850273132},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6366000175476074},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5839999914169312},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5633999705314636},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.5248000025749207},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.504800021648407},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.4650999903678894},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.44909998774528503},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.4417000114917755},{"id":"https://openalex.org/C2781099131","wikidata":"https://www.wikidata.org/wiki/Q744385","display_name":"Temporal lobe","level":3,"score":0.4165000021457672},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.39980000257492065},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.36320000886917114},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3467000126838684},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3287000060081482},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C2775842073","wikidata":"https://www.wikidata.org/wiki/Q208376","display_name":"Positron emission tomography","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C141516989","wikidata":"https://www.wikidata.org/wiki/Q1182555","display_name":"Default mode network","level":3,"score":0.27489998936653137},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C2993858690","wikidata":"https://www.wikidata.org/wiki/Q744385","display_name":"Temporal cortex","level":2,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.28397","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28397","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.28397","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.28397","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":"Preprint"},"sustainable_development_goals":[{"score":0.7565575242042542,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Predicting":[0],"conversion":[1,96,190],"from":[2],"Mild":[3],"Cognitive":[4],"Impairment":[5],"(MCI)":[6],"to":[7,53,70,157,189],"Alzheimer's":[8,88],"Disease":[9,89],"(AD)":[10],"is":[11,55],"critical":[12],"for":[13,93],"early":[14],"intervention.":[15],"Current":[16],"deep":[17],"learning":[18],"paradigms":[19],"predominantly":[20],"rely":[21],"on":[22,86],"cross-sectional":[23],"structural":[24,76,110],"MRI,":[25,111],"neglecting":[26],"prognostic":[27],"value":[28],"in":[29,170],"patient-specific":[30,68],"anatomical":[31],"trajectories.":[32],"We":[33],"introduce":[34],"the":[35,87,100,114,171,178],"Temporal":[36,57,64],"Adaptive":[37,63],"Fusion":[38,58],"Network":[39],"(TAF-Net),":[40],"a":[41,56,137],"hybrid":[42],"CNN-Transformer":[43],"architecture":[44,128],"that":[45,145],"models":[46],"paired":[47],"longitudinal":[48,146],"3D":[49],"MRI":[50],"scans.":[51],"Central":[52],"TAF-Net":[54,98],"Module":[59],"governed":[60],"by":[61,154],"an":[62],"Gate,":[65],"which":[66],"learns":[67],"weightings":[69],"synthesize":[71],"three":[72],"spatiotemporal":[73],"representations:":[74],"explicit":[75,182],"change,":[77],"region-to-region":[78],"temporal":[79,173],"cross-attention,":[80],"and":[81,117,175],"bilateral":[82],"feature":[83],"concatenation.":[84],"Evaluated":[85],"Neuroimaging":[90],"Initiative":[91],"cohort":[92],"three-year":[94],"MCI-to-AD":[95],"prediction,":[97],"achieved":[99],"highest":[101],"discriminative":[102],"performance":[103,135],"among":[104],"all":[105],"evaluated":[106],"methods":[107,120],"using":[108],"only":[109],"significantly":[112],"outperforming":[113],"strongest":[115],"baseline":[116,134],"approaching":[118],"multimodal":[119],"requiring":[121],"PET,":[122],"CSF,":[123],"or":[124],"genetic":[125],"data.":[126,141],"The":[127],"exhibited":[129],"exceptional":[130],"data":[131],"efficiency,":[132],"matching":[133],"with":[136,166,185],"fraction":[138],"of":[139],"training":[140],"Ablation":[142],"studies":[143],"demonstrate":[144],"fusion":[147],"improves":[148],"discrimination":[149],"while":[150,177],"reducing":[151],"predictive":[152],"variance":[153],"48%":[155],"compared":[156],"single-timepoint":[158],"evaluation.":[159],"Interpretability":[160],"analyses":[161],"reveal":[162],"spatial":[163],"attention":[164],"aligned":[165],"established":[167],"AD":[168],"pathology":[169],"medial":[172],"lobe":[174],"ventricles,":[176],"gating":[179],"mechanism":[180],"prioritizes":[181],"volumetric":[183],"change":[184],"strong":[186],"positive":[187],"correlation":[188],"risk.":[191]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-29T00:00:00"}
