{"id":"https://openalex.org/W7133334021","doi":"https://doi.org/10.48550/arxiv.2603.00756","title":"Stroke outcome and evolution prediction from CT brain using a spatiotemporal diffusion autoencoder","display_name":"Stroke outcome and evolution prediction from CT brain using a spatiotemporal diffusion autoencoder","publication_year":2026,"publication_date":"2026-02-28","ids":{"openalex":"https://openalex.org/W7133334021","doi":"https://doi.org/10.48550/arxiv.2603.00756"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.00756","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00756","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2603.00756","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127998710","display_name":"Adam Marcus","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marcus, Adam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128015212","display_name":"Paul Bentley","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bentley, Paul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127981079","display_name":"Daniel Rueckert","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rueckert, Daniel","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/T10227","display_name":"Acute Ischemic Stroke Management","score":0.4153999984264374,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T10227","display_name":"Acute Ischemic Stroke Management","score":0.4153999984264374,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.12970000505447388,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.10750000178813934,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/stroke","display_name":"Stroke (engine)","score":0.7177000045776367},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6516000032424927},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.5922999978065491},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5329999923706055},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.47679999470710754},{"id":"https://openalex.org/keywords/radiomics","display_name":"Radiomics","score":0.37389999628067017},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.3458000123500824},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3402000069618225}],"concepts":[{"id":"https://openalex.org/C2780645631","wikidata":"https://www.wikidata.org/wiki/Q671554","display_name":"Stroke (engine)","level":2,"score":0.7177000045776367},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6516000032424927},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.5922999978065491},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.590499997138977},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5329999923706055},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48429998755455017},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.47679999470710754},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4133000075817108},{"id":"https://openalex.org/C2778559731","wikidata":"https://www.wikidata.org/wiki/Q23808793","display_name":"Radiomics","level":2,"score":0.37389999628067017},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34689998626708984},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3458000123500824},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C149550507","wikidata":"https://www.wikidata.org/wiki/Q899360","display_name":"Diffusion MRI","level":3,"score":0.3319999873638153},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.32760000228881836},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.302700012922287},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C2992477034","wikidata":"https://www.wikidata.org/wiki/Q83042","display_name":"Clinical neurology","level":2,"score":0.2757999897003174},{"id":"https://openalex.org/C2776361831","wikidata":"https://www.wikidata.org/wiki/Q10681911","display_name":"Stroke recovery","level":3,"score":0.2709999978542328},{"id":"https://openalex.org/C535046627","wikidata":"https://www.wikidata.org/wiki/Q30612","display_name":"Clinical trial","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C3020166492","wikidata":"https://www.wikidata.org/wiki/Q12202","display_name":"Acute stroke","level":3,"score":0.26010000705718994}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.00756","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00756","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2603.00756","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00756","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[{"id":"https://metadata.un.org/sdg/16","score":0.72930508852005,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Stroke":[0],"is":[1,105],"a":[2,32,51,70,108],"major":[3],"cause":[4],"of":[5,34,47,64,102,111],"death":[6],"and":[7,12,36,94,139],"disability":[8],"worldwide.":[9],"Accurate":[10],"outcome":[11,141],"evolution":[13],"prediction":[14],"has":[15],"the":[16,37,44,62,88,95,132],"potential":[17],"to":[18,27,68,90],"revolutionize":[19],"stroke":[20,74,98],"care":[21],"by":[22,41,86],"individualizing":[23],"clinical":[24],"decision-making":[25],"leading":[26],"better":[28],"outcomes.":[29],"However,":[30],"despite":[31],"plethora":[33],"attempts":[35],"rich":[38],"data":[39],"provided":[40],"neuroimaging,":[42],"modelling":[43],"ultimate":[45],"fate":[46],"brain":[48],"tissue":[49],"remains":[50],"challenging":[52],"task.":[53],"In":[54],"this":[55,84],"work,":[56],"we":[57],"apply":[58],"recent":[59],"ideas":[60],"in":[61],"field":[63],"diffusion":[65],"probabilistic":[66],"models":[67],"generate":[69],"self-supervised":[71],"semantically":[72],"meaningful":[73],"representation":[75,85],"from":[76,97,115],"Computed":[77],"Tomography":[78],"(CT)":[79],"images.":[80],"We":[81],"then":[82],"improve":[83],"extending":[87],"method":[89,130],"accommodate":[91],"longitudinal":[92],"images":[93,114],"time":[96],"onset.":[99],"The":[100],"effectiveness":[101],"our":[103,129],"approach":[104],"evaluated":[106],"on":[107],"dataset":[109],"consisting":[110],"5,824":[112],"CT":[113],"3,573":[116],"patients":[117],"across":[118],"two":[119],"medical":[120],"centers":[121],"with":[122],"minimal":[123],"labels.":[124],"Comparative":[125],"experiments":[126],"show":[127],"that":[128],"achieves":[131],"best":[133],"performance":[134],"for":[135],"predicting":[136],"next-day":[137],"severity":[138],"functional":[140],"at":[142],"discharge.":[143]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-04T00:00:00"}
