{"id":"https://openalex.org/W4404450758","doi":"https://doi.org/10.48550/arxiv.2411.09361","title":"Time-to-Event Pretraining for 3D Medical Imaging","display_name":"Time-to-Event Pretraining for 3D Medical Imaging","publication_year":2024,"publication_date":"2024-11-14","ids":{"openalex":"https://openalex.org/W4404450758","doi":"https://doi.org/10.48550/arxiv.2411.09361"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2411.09361","pdf_url":"http://arxiv.org/pdf/2411.09361","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://arxiv.org/pdf/2411.09361","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078410427","display_name":"Zepeng Huo","orcid":"https://orcid.org/0000-0001-8920-1690"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huo, Zepeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028277225","display_name":"Jason Fries","orcid":"https://orcid.org/0000-0001-9316-5768"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fries, Jason Alan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004992575","display_name":"Alejandro Lozano","orcid":"https://orcid.org/0000-0002-1475-0676"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lozano, Alejandro","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062008578","display_name":"Jeya Maria Jose Valanarasu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Valanarasu, Jeya Maria Jose","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010316094","display_name":"Ethan Steinberg","orcid":"https://orcid.org/0000-0001-7166-5032"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Steinberg, Ethan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025304724","display_name":"Louis Blankemeier","orcid":"https://orcid.org/0000-0001-6365-9767"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Blankemeier, Louis","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064829377","display_name":"Akshay Chaudhari","orcid":"https://orcid.org/0000-0002-3667-6796"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chaudhari, Akshay S.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087710258","display_name":"Curtis P. Langlotz","orcid":"https://orcid.org/0000-0002-8972-8051"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Langlotz, Curtis","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5041175834","display_name":"Nigam H. Shah","orcid":"https://orcid.org/0000-0001-9385-7158"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shah, Nigam H.","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"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":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":84},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10358","display_name":"Advanced Radiotherapy Techniques","score":0.9836,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10358","display_name":"Advanced Radiotherapy Techniques","score":0.9836,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11361","display_name":"Digital Radiography and Breast Imaging","score":0.9814,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory 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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9765,"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":[],"concepts":[{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6179799},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.36270708},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3493153},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.34572932},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.23575968},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09165987},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2411.09361","pdf_url":"http://arxiv.org/pdf/2411.09361","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2411.09361","pdf_url":"http://arxiv.org/pdf/2411.09361","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4396701345","https://openalex.org/W4396696052","https://openalex.org/W4391913857","https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2376932109","https://openalex.org/W2358668433","https://openalex.org/W2001405890"],"abstract_inverted_index":{"With":[0],"the":[1,8,65,171],"rise":[2],"of":[3,11,26,119,132,145],"medical":[4,36,101],"foundation":[5,172],"models":[6,38,103],"and":[7,85,127,147,177],"growing":[9],"availability":[10],"imaging":[12,23,37,102,179],"data,":[13],"scalable":[14],"pretraining":[15,97],"techniques":[16],"offer":[17],"a":[18,58,96,117,148],"promising":[19],"way":[20],"to":[21,48,57,69,181],"identify":[22,70],"biomarkers":[24,51,71],"predictive":[25],"future":[27],"disease":[28,74],"risk.":[29],"While":[30],"current":[31],"self-supervised":[32],"methods":[33],"for":[34,99,173],"3D":[35,100,178],"capture":[39],"local":[40],"structural":[41],"features":[42],"like":[43],"organ":[44],"morphology,":[45],"they":[46,77],"fail":[47],"link":[49],"pixel":[50],"with":[52,73],"long-term":[53],"health":[54,113],"outcomes":[55],"due":[56],"missing":[59],"context":[60,67],"problem.":[61],"Current":[62],"approaches":[63],"lack":[64],"temporal":[66,107],"necessary":[68],"correlated":[72],"progression,":[75],"as":[76],"rely":[78],"on":[79],"supervision":[80,108],"derived":[81],"only":[82],"from":[83,109],"images":[84],"concurrent":[86],"text":[87],"descriptions.":[88],"To":[89],"address":[90],"this,":[91],"we":[92],"introduce":[93],"time-to-event":[94,128],"pretraining,":[95],"framework":[98],"that":[104],"leverages":[105],"large-scale":[106],"paired,":[110],"longitudinal":[111,175],"electronic":[112],"records":[114],"(EHRs).":[115],"Using":[116],"dataset":[118],"18,945":[120],"CT":[121],"scans":[122],"(4.2":[123],"million":[124],"2D":[125],"images)":[126],"distributions":[129],"across":[130,154],"thousands":[131],"EHR-derived":[133],"tasks,":[134],"our":[135],"method":[136],"improves":[137],"outcome":[138],"prediction,":[139],"achieving":[140],"an":[141],"average":[142],"AUROC":[143],"increase":[144],"23.7%":[146],"29.4%":[149],"gain":[150],"in":[151],"Harrell's":[152],"C-index":[153],"8":[155],"benchmark":[156],"tasks.":[157],"Importantly,":[158],"these":[159],"gains":[160],"are":[161],"achieved":[162],"without":[163],"sacrificing":[164],"diagnostic":[165],"classification":[166],"performance.":[167],"This":[168],"study":[169],"lays":[170],"integrating":[174],"EHR":[176],"data":[180],"advance":[182],"clinical":[183],"risk":[184],"prediction.":[185]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4404450758","counts_by_year":[],"updated_date":"2024-12-24T01:55:09.342284","created_date":"2024-11-17"}