{"id":"https://openalex.org/W7138278841","doi":"https://doi.org/10.48550/arxiv.2603.13590","title":"Opportunistic Cardiac Health Assessment: Estimating Phenotypes from Localizer MRI through Multi-Modal Representations","display_name":"Opportunistic Cardiac Health Assessment: Estimating Phenotypes from Localizer MRI through Multi-Modal Representations","publication_year":2026,"publication_date":"2026-03-13","ids":{"openalex":"https://openalex.org/W7138278841","doi":"https://doi.org/10.48550/arxiv.2603.13590"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.13590","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13590","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.2603.13590","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129693726","display_name":"Busra Nur Zeybek","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zeybek, Busra Nur","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111287730","display_name":"\u00d6zg\u00fcn Turgut","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Turgut, \u00d6zg\u00fcn","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129673930","display_name":"Yundi Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yundi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129745575","display_name":"Jiazhen Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Jiazhen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129713914","display_name":"Robert Graf","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Graf, Robert","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025908540","display_name":"Sophie Starck","orcid":"https://orcid.org/0000-0003-2495-6114"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Starck, Sophie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129714837","display_name":"Daniel Rueckert","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rueckert, Daniel","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5123493400","display_name":"Sevgi Gokce Kafali","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kafali, Sevgi Gokce","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5129693726"],"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/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.41200000047683716,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.41200000047683716,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T10217","display_name":"Cardiac electrophysiology and arrhythmias","score":0.07370000332593918,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.07339999824762344,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/inference","display_name":"Inference","score":0.6202999949455261},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5769000053405762},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5622000098228455},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5511999726295471},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5123000144958496},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.4674000144004822},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.43959999084472656},{"id":"https://openalex.org/keywords/cardiac-magnetic-resonance","display_name":"Cardiac magnetic resonance","score":0.42309999465942383}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6202999949455261},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6078000068664551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6011999845504761},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5769000053405762},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5622000098228455},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5511999726295471},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5123000144958496},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4553999900817871},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.43959999084472656},{"id":"https://openalex.org/C2987145844","wikidata":"https://www.wikidata.org/wiki/Q5038325","display_name":"Cardiac magnetic resonance","level":3,"score":0.42309999465942383},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.41040000319480896},{"id":"https://openalex.org/C40993552","wikidata":"https://www.wikidata.org/wiki/Q514654","display_name":"Gold standard (test)","level":2,"score":0.3716000020503998},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34549999237060547},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.3425000011920929},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.33730000257492065},{"id":"https://openalex.org/C164614171","wikidata":"https://www.wikidata.org/wiki/Q5204775","display_name":"DECIPHER","level":2,"score":0.3345000147819519},{"id":"https://openalex.org/C2776008845","wikidata":"https://www.wikidata.org/wiki/Q5038325","display_name":"Cardiac magnetic resonance imaging","level":3,"score":0.3303999900817871},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29829999804496765},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2921000123023987},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.28610000014305115},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.27239999175071716},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.13590","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13590","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.2603.13590","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13590","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Cardiovascular":[0],"diseases":[1],"are":[2,14,24,56,92,181,232],"the":[3,15,86,101,105,192,197,204],"leading":[4],"cause":[5],"of":[6,65,104,176],"death.":[7],"Cardiac":[8],"phenotypes":[9],"(CPs),":[10],"e.g.,":[11],"ejection":[12],"fraction,":[13],"gold":[16],"standard":[17],"for":[18,52,114,208,227,244],"assessing":[19],"cardiac":[20,28,87],"health,":[21],"but":[22],"they":[23],"derived":[25],"from":[26,159,166],"cine":[27],"magnetic":[29,42],"resonance":[30,43],"imaging":[31],"(CMR),":[32],"which":[33,55],"is":[34],"costly":[35],"and":[36,49,63,83,99,126,135,156,161,224,235],"requires":[37],"high":[38,225],"spatio-temporal":[39],"resolution.":[40],"Every":[41],"(MR)":[44],"examination":[45],"begins":[46],"with":[47,211],"rapid":[48,234],"coarse":[50],"localizers":[51,68,231],"scan":[53],"planning,":[54],"discarded":[57],"thereafter.":[58],"Despite":[59],"non-diagnostic":[60],"image":[61],"quality":[62],"lack":[64],"temporal":[66,102,157],"information,":[67,80],"can":[69],"provide":[70],"valuable":[71],"structural":[72,228],"information":[73,158],"rapidly.":[74],"In":[75],"addition":[76],"to":[77,129,145,184,195],"imaging,":[78],"patient-level":[79],"including":[81],"demographics":[82],"lifestyle,":[84],"influence":[85],"health":[88],"assessment.":[89],"Electrocardiograms":[90],"(ECGs)":[91],"inexpensive,":[93],"routinely":[94],"ordered":[95],"in":[96],"clinical":[97],"practice,":[98],"capture":[100],"activity":[103],"heart.":[106],"Here,":[107],"we":[108,152],"introduce":[109],"C-TRIP":[110,219,238],"(Cardiac":[111],"Tri-modal":[112],"Representations":[113],"Imaging":[115],"Phenotypes),":[116],"a":[117,131],"multi-modal":[118],"framework":[119,239],"that":[120],"aligns":[121],"localizer":[122,139,216],"MRI,":[123],"ECG":[124],"signals,":[125],"tabular":[127,171],"metadata":[128],"learn":[130,185],"robust":[132],"latent":[133,198],"space":[134,207],"predict":[136],"CPs":[137],"using":[138],"images":[140],"as":[141],"an":[142],"opportunistic":[143],"alternative":[144],"CMR.":[146],"By":[147],"combining":[148],"these":[149],"three":[150,177],"modalities,":[151],"leverage":[153],"cheap":[154],"spatial":[155],"localizers,":[160],"ECG,":[162],"respectively":[163],"while":[164],"benefiting":[165],"patient-specific":[167],"context":[168],"provided":[169],"by":[170],"data.":[172],"Our":[173],"pipeline":[174],"consists":[175],"stages.":[178],"First,":[179],"encoders":[180,194],"trained":[182],"independently":[183],"uni-modal":[186],"representations.":[187],"The":[188,200],"second":[189],"stage":[190,202],"fuses":[191],"pre-trained":[193],"unify":[196],"space.":[199],"final":[201],"uses":[203],"enriched":[205],"representation":[206],"CP":[209,245],"prediction,":[210],"inference":[212],"performed":[213],"exclusively":[214],"on":[215],"MRI.":[217],"Proposed":[218],"yields":[220],"accurate":[221],"functional":[222],"CPs,":[223],"correlations":[226],"CPs.":[229],"Since":[230],"inherently":[233],"low-cost,":[236],"our":[237],"could":[240],"enable":[241],"better":[242],"accessibility":[243],"estimation.":[246]},"counts_by_year":[],"updated_date":"2026-03-18T06:31:55.123368","created_date":"2026-03-18T00:00:00"}
