{"id":"https://openalex.org/W7133548643","doi":"https://doi.org/10.48550/arxiv.2603.02434","title":"MIRAGE: Knowledge Graph-Guided Cross-Cohort MRI Synthesis for Alzheimer's Disease Prediction","display_name":"MIRAGE: Knowledge Graph-Guided Cross-Cohort MRI Synthesis for Alzheimer's Disease Prediction","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7133548643","doi":"https://doi.org/10.48550/arxiv.2603.02434"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.02434","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.02434","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2603.02434","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067651547","display_name":"Guanchen Wu","orcid":"https://orcid.org/0000-0002-5579-1052"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wu, Guanchen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128070372","display_name":"Zhe Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Zhe","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103326051","display_name":"Yuzhang Xie","orcid":"https://orcid.org/0009-0001-3241-9418"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Yuzhang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128042363","display_name":"Runze Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Runze","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023164534","display_name":"Akul Chopra","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chopra, Akul","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128112063","display_name":"Deqiang Qiu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiu, Deqiang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128060572","display_name":"Xiao Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Xiao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128089719","display_name":"Fei Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Fei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128040634","display_name":"Carl Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Carl","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5067651547"],"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/T13702","display_name":"Machine Learning in Healthcare","score":0.5622000098228455,"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"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.5622000098228455,"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"}},{"id":"https://openalex.org/T10009","display_name":"Dementia and Cognitive Impairment Research","score":0.18410000205039978,"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":0.08190000057220459,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.49810001254081726},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46299999952316284},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.3962000012397766},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.3869999945163727},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38690000772476196},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.38089999556541443},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.3783999979496002},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.3619999885559082},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.35199999809265137},{"id":"https://openalex.org/keywords/directed-acyclic-graph","display_name":"Directed acyclic graph","score":0.35179999470710754}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.695900022983551},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5687000155448914},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.49810001254081726},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46299999952316284},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.3962000012397766},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3869999945163727},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38690000772476196},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.38089999556541443},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.3783999979496002},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3774000108242035},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3619999885559082},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.35179999470710754},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.35109999775886536},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.34040001034736633},{"id":"https://openalex.org/C2777852691","wikidata":"https://www.wikidata.org/wiki/Q13430821","display_name":"Crowds","level":2,"score":0.3257000148296356},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.31360000371932983},{"id":"https://openalex.org/C2776673561","wikidata":"https://www.wikidata.org/wiki/Q655357","display_name":"Atlas (anatomy)","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.30090001225471497},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.28949999809265137},{"id":"https://openalex.org/C3020144179","wikidata":"https://www.wikidata.org/wiki/Q10871684","display_name":"Electronic health record","level":3,"score":0.28850001096725464},{"id":"https://openalex.org/C197115733","wikidata":"https://www.wikidata.org/wiki/Q1003136","display_name":"Forcing (mathematics)","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2524999976158142},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.02434","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.02434","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.02434","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.02434","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reliable":[0],"Alzheimer's":[1],"disease":[2],"(AD)":[3],"diagnosis":[4],"increasingly":[5],"relies":[6],"on":[7],"multimodal":[8],"assessments":[9],"combining":[10],"structural":[11,157],"Magnetic":[12],"Resonance":[13],"Imaging":[14],"(MRI)":[15],"and":[16,35,57,91,123],"Electronic":[17],"Health":[18],"Records":[19],"(EHR).":[20],"However,":[21],"deploying":[22],"these":[23],"models":[24],"is":[25,54],"bottlenecked":[26],"by":[27,143,202],"modality":[28],"missingness,":[29],"as":[30,76,137,154],"MRI":[31],"scans":[32,48],"are":[33],"expensive":[34,183],"frequently":[36],"unavailable":[37],"in":[38,208],"many":[39],"patient":[40],"cohorts.":[41],"Furthermore,":[42],"synthesizing":[43],"de":[44],"novo":[45],"3D":[46,133,184],"anatomical":[47],"from":[49,109],"sparse,":[50],"high-dimensional":[51],"tabular":[52],"records":[53],"technically":[55],"challenging":[56],"poses":[58],"severe":[59],"clinical":[60],"risks.":[61],"To":[62,118],"address":[63],"this,":[64],"we":[65,128],"introduce":[66],"MIRAGE,":[67],"a":[68,86,101,130,144,155],"novel":[69,145],"framework":[70,191],"that":[71,105,189],"reframes":[72],"the":[73,120,194,198],"missing-MRI":[74],"problem":[75],"an":[77,138],"anatomy-guided":[78],"cross-modal":[79],"latent":[80,161],"distillation":[81],"task.":[82],"First,":[83],"MIRAGE":[84,179],"leverages":[85],"Biomedical":[87],"Knowledge":[88],"Graph":[89,92],"(KG)":[90],"Attention":[93],"Networks":[94],"to":[95,114,163,205],"map":[96],"heterogeneous":[97],"EHR":[98],"variables":[99],"into":[100],"unified":[102],"embedding":[103],"space":[104],"can":[106],"be":[107],"propagated":[108],"cohorts":[110,115,209],"with":[111],"real":[112,211],"MRIs":[113],"without":[116,210],"them.":[117],"bridge":[119],"semantic":[121],"gap":[122],"enforce":[124],"physical":[125],"spatial":[126],"awareness,":[127],"employ":[129],"frozen":[131],"pre-trained":[132],"U-Net":[134],"decoder":[135,152],"strictly":[136],"auxiliary":[139],"regularization":[140],"engine.":[141],"Supported":[142],"cohort-aggregated":[146],"skip":[147],"feature":[148],"compensation":[149],"strategy,":[150],"this":[151,173],"acts":[153],"rigorous":[156],"penalty,":[158],"forcing":[159],"1D":[160],"representations":[162],"encode":[164],"biologically":[165],"plausible,":[166],"macro-level":[167],"pathological":[168],"semantics.":[169],"By":[170],"exclusively":[171],"utilizing":[172],"distilled":[174],"\"diagnostic-surrogate\"":[175],"representation":[176],"during":[177],"inference,":[178],"completely":[180],"bypasses":[181],"computationally":[182],"voxel":[185],"reconstruction.":[186],"Experiments":[187],"demonstrate":[188],"our":[190],"successfully":[192],"bridges":[193],"missing-modality":[195],"gap,":[196],"improving":[197],"AD":[199],"classification":[200],"rate":[201],"13%":[203],"compared":[204],"unimodal":[206],"baselines":[207],"MRIs.":[212]},"counts_by_year":[],"updated_date":"2026-03-05T07:36:02.291473","created_date":"2026-03-05T00:00:00"}