{"id":"https://openalex.org/W7162657644","doi":"https://doi.org/10.1007/s12065-026-01202-6","title":"Artificial intelligence for early detection of pancreatic cancer: pre-diagnostic detection across imaging, biomarkers, and EHRs: a systematic review","display_name":"Artificial intelligence for early detection of pancreatic cancer: pre-diagnostic detection across imaging, biomarkers, and EHRs: a systematic review","publication_year":2026,"publication_date":"2026-05-28","ids":{"openalex":"https://openalex.org/W7162657644","doi":"https://doi.org/10.1007/s12065-026-01202-6"},"language":"en","primary_location":{"id":"doi:10.1007/s12065-026-01202-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12065-026-01202-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12065-026-01202-6.pdf","source":{"id":"https://openalex.org/S182392644","display_name":"Evolutionary Intelligence","issn_l":"1864-5909","issn":["1864-5909","1864-5917"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Evolutionary Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s12065-026-01202-6.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137307505","display_name":"Vaia Apostolou","orcid":null},"institutions":[{"id":"https://openalex.org/I183898223","display_name":"International Hellenic University","ror":"https://ror.org/00708jp83","country_code":"GR","type":"education","lineage":["https://openalex.org/I183898223"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Vaia Apostolou","raw_affiliation_strings":["The Data Mining & Analytics Research Group, School of Science and Technology, International Hellenic University, 14th km, N. Moudania, Thermi, 57001, Thessaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Data Mining & Analytics Research Group, School of Science and Technology, International Hellenic University, 14th km, N. Moudania, Thermi, 57001, Thessaloniki, Greece","institution_ids":["https://openalex.org/I183898223"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137282064","display_name":"George Papageorgiou","orcid":"https://orcid.org/0000-0002-9361-8621"},"institutions":[{"id":"https://openalex.org/I183898223","display_name":"International Hellenic University","ror":"https://ror.org/00708jp83","country_code":"GR","type":"education","lineage":["https://openalex.org/I183898223"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"George Papageorgiou","raw_affiliation_strings":["The Data Mining & Analytics Research Group, School of Science and Technology, International Hellenic University, 14th km, N. Moudania, Thermi, 57001, Thessaloniki, Greece"],"raw_orcid":"https://orcid.org/0000-0002-9361-8621","affiliations":[{"raw_affiliation_string":"The Data Mining & Analytics Research Group, School of Science and Technology, International Hellenic University, 14th km, N. Moudania, Thermi, 57001, Thessaloniki, Greece","institution_ids":["https://openalex.org/I183898223"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071901091","display_name":"Christos Tjortjis","orcid":"https://orcid.org/0000-0001-8263-9024"},"institutions":[{"id":"https://openalex.org/I183898223","display_name":"International Hellenic University","ror":"https://ror.org/00708jp83","country_code":"GR","type":"education","lineage":["https://openalex.org/I183898223"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Christos Tjortjis","raw_affiliation_strings":["The Data Mining & Analytics Research Group, School of Science and Technology, International Hellenic University, 14th km, N. Moudania, Thermi, 57001, Thessaloniki, Greece"],"raw_orcid":"https://orcid.org/0000-0001-8263-9024","affiliations":[{"raw_affiliation_string":"The Data Mining & Analytics Research Group, School of Science and Technology, International Hellenic University, 14th km, N. Moudania, Thermi, 57001, Thessaloniki, Greece","institution_ids":["https://openalex.org/I183898223"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5071901091"],"corresponding_institution_ids":["https://openalex.org/I183898223"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.90829302,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10231","display_name":"Pancreatic and Hepatic Oncology Research","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T10231","display_name":"Pancreatic and Hepatic Oncology Research","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T10862","display_name":"AI in cancer detection","score":0.00139999995008111,"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/T10760","display_name":"Pancreatitis Pathology and Treatment","score":0.0007999999797903001,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.5001999735832214},{"id":"https://openalex.org/keywords/triage","display_name":"Triage","score":0.4903999865055084},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.4731000065803528},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.46239998936653137},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.39169999957084656},{"id":"https://openalex.org/keywords/clinical-practice","display_name":"Clinical Practice","score":0.36480000615119934},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3522000014781952}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6531999707221985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.592199981212616},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5317999720573425},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.5001999735832214},{"id":"https://openalex.org/C2777120189","wikidata":"https://www.wikidata.org/wiki/Q780067","display_name":"Triage","level":2,"score":0.4903999865055084},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.4731000065803528},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.46239998936653137},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.39169999957084656},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.36480000615119934},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3522000014781952},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.35089999437332153},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3422999978065491},{"id":"https://openalex.org/C157170001","wikidata":"https://www.wikidata.org/wiki/Q4781507","display_name":"Applications of artificial intelligence","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.3206000030040741},{"id":"https://openalex.org/C2781197716","wikidata":"https://www.wikidata.org/wiki/Q864574","display_name":"Biomarker","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28299999237060547},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.2680000066757202},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.2599000036716461},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25920000672340393}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s12065-026-01202-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12065-026-01202-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12065-026-01202-6.pdf","source":{"id":"https://openalex.org/S182392644","display_name":"Evolutionary Intelligence","issn_l":"1864-5909","issn":["1864-5909","1864-5917"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Evolutionary Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s12065-026-01202-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12065-026-01202-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12065-026-01202-6.pdf","source":{"id":"https://openalex.org/S182392644","display_name":"Evolutionary Intelligence","issn_l":"1864-5909","issn":["1864-5909","1864-5917"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Evolutionary Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.5871366262435913,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7162657644.pdf","grobid_xml":"https://content.openalex.org/works/W7162657644.grobid-xml"},"referenced_works_count":106,"referenced_works":["https://openalex.org/W2965010580","https://openalex.org/W2982364478","https://openalex.org/W2985984046","https://openalex.org/W2995984299","https://openalex.org/W3020417958","https://openalex.org/W3021538281","https://openalex.org/W3023640369","https://openalex.org/W3030432638","https://openalex.org/W3048208816","https://openalex.org/W3081515813","https://openalex.org/W3084298108","https://openalex.org/W3086692350","https://openalex.org/W3093095586","https://openalex.org/W3108518974","https://openalex.org/W3136362669","https://openalex.org/W3164089558","https://openalex.org/W3164989533","https://openalex.org/W3169906946","https://openalex.org/W3176719936","https://openalex.org/W3194599467","https://openalex.org/W3198653501","https://openalex.org/W3213012553","https://openalex.org/W3214040596","https://openalex.org/W4200602534","https://openalex.org/W4210672352","https://openalex.org/W4210796773","https://openalex.org/W4214483633","https://openalex.org/W4220692708","https://openalex.org/W4220816106","https://openalex.org/W4221019801","https://openalex.org/W4280548574","https://openalex.org/W4283780227","https://openalex.org/W4286264999","https://openalex.org/W4294094030","https://openalex.org/W4294218763","https://openalex.org/W4295435240","https://openalex.org/W4304617403","https://openalex.org/W4306168050","https://openalex.org/W4306700527","https://openalex.org/W4306834757","https://openalex.org/W4310855430","https://openalex.org/W4313575282","https://openalex.org/W4319315981","https://openalex.org/W4360820289","https://openalex.org/W4362458190","https://openalex.org/W4362684579","https://openalex.org/W4366170893","https://openalex.org/W4375858857","https://openalex.org/W4376642418","https://openalex.org/W4377200874","https://openalex.org/W4378571658","https://openalex.org/W4379768917","https://openalex.org/W4380047793","https://openalex.org/W4380785244","https://openalex.org/W4380927628","https://openalex.org/W4381741324","https://openalex.org/W4382203270","https://openalex.org/W4383722085","https://openalex.org/W4384405782","https://openalex.org/W4385407083","https://openalex.org/W4385498079","https://openalex.org/W4385703448","https://openalex.org/W4386295956","https://openalex.org/W4387393350","https://openalex.org/W4387447774","https://openalex.org/W4387489745","https://openalex.org/W4388573997","https://openalex.org/W4388828550","https://openalex.org/W4388834713","https://openalex.org/W4388848645","https://openalex.org/W4388864626","https://openalex.org/W4389004714","https://openalex.org/W4389215703","https://openalex.org/W4390421260","https://openalex.org/W4391842283","https://openalex.org/W4392005629","https://openalex.org/W4393098193","https://openalex.org/W4393205832","https://openalex.org/W4394617272","https://openalex.org/W4395009760","https://openalex.org/W4396529035","https://openalex.org/W4396544408","https://openalex.org/W4396956689","https://openalex.org/W4399755928","https://openalex.org/W4399915605","https://openalex.org/W4401507568","https://openalex.org/W4401722210","https://openalex.org/W4401966708","https://openalex.org/W4401988219","https://openalex.org/W4402005590","https://openalex.org/W4402020416","https://openalex.org/W4402231850","https://openalex.org/W4402949379","https://openalex.org/W4403699844","https://openalex.org/W4404421794","https://openalex.org/W4404606255","https://openalex.org/W4404970884","https://openalex.org/W4405073270","https://openalex.org/W4405703822","https://openalex.org/W4406431707","https://openalex.org/W4407992160","https://openalex.org/W4409454795","https://openalex.org/W4411301111","https://openalex.org/W4412977292","https://openalex.org/W4413013084","https://openalex.org/W4413187992"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Pancreatic":[1],"Ductal":[2],"Adenocarcinoma":[3],"(PDAC)":[4],"is":[5,15],"highly":[6],"lethal,":[7],"yet":[8],"outcomes":[9],"improve":[10],"markedly":[11],"when":[12],"the":[13,67,122,126,190,232,236],"disease":[14],"detected":[16,215],"at":[17,201],"its":[18],"earliest":[19],"stages.":[20],"This":[21],"systematic":[22],"review":[23],"synthesizes":[24],"recent":[25],"applications":[26],"of":[27,70,128,170,179],"Artificial":[28],"Intelligence":[29],"(AI)":[30],"and":[31,50,59,66,73,95,113,142,147,166,176,206],"Machine":[32],"Learning":[33],"(ML)":[34],"for":[35,109,238],"clinically":[36],"actionable":[37],"early":[38],"detection":[39],"across":[40],"three":[41],"data":[42,105],"streams:":[43],"medical":[44],"imaging,":[45],"Electronic":[46],"Health":[47],"Records":[48],"(EHRs),":[49],"liquid-biopsy":[51],"biomarkers.":[52],"We":[53],"surveyed":[54],"studies":[55,184],"published":[56],"between":[57],"2020":[58],"mid-2025,":[60],"emphasizing":[61],"task":[62],"design,":[63],"validation":[64],"strategies,":[65],"authors\u2019":[68],"description":[69],"model":[71],"reliability":[72],"deployment.":[74],"Across":[75,182],"modalities,":[76,183],"retrospective":[77],"evidence":[78],"indicates":[79],"that":[80],"AI":[81,213],"can":[82],"surface":[83],"weak,":[84],"distributed":[85],"signals,":[86],"preceding":[87],"overt":[88],"radiologic":[89],"findings,":[90],"support":[91],"challenging":[92],"differential":[93],"diagnoses,":[94],"aid":[96],"procedure-level":[97],"verification.":[98,153],"EHR-based":[99],"population":[100],"pre-filtering":[101],"(triage":[102],"via":[103],"routine":[104],"to":[106],"select":[107],"patients":[108],"imaging)":[110],"shows":[111],"promise,":[112,233],"biomarker-driven":[114],"approaches":[115],"typically":[116],"outperform":[117],"single-analyte":[118],"baselines.":[119],"Taken":[120],"together,":[121],"current":[123],"literature":[124],"supports":[125],"possibility":[127],"a":[129,222],"pragmatic,":[130],"tiered":[131],"workflow,":[132],"in":[133,163,204,210],"which":[134],"EHR/biomarker":[135],"triage":[136],"directs":[137],"confirmatory":[138],"Computed":[139],"Tomography":[140],"(CT)":[141],"Magnetic":[143],"Resonance":[144],"Imaging":[145],"(MRI)":[146],"where":[148],"indicated,":[149],"Endoscopic":[150],"Ultrasound":[151],"(EUS)-guided":[152],"Clinical":[154],"implementation":[155],"remains":[156],"constrained":[157],"by":[158],"limited":[159],"external":[160],"validation,":[161],"variability":[162],"imaging":[164],"protocols":[165],"biomarker":[167],"assays,":[168],"lack":[169],"clinical-utility":[171],"analysis":[172],"(decision-curve":[173],"net":[174],"benefit),":[175],"sparse":[177],"reporting":[178],"subgroup":[180],"outcomes.":[181],"frequently":[185],"report":[186],"good":[187],"Area":[188],"Under":[189],"Receiver":[191],"Operating":[192],"Characteristic":[193],"Curve":[194],"(AUROC)-based":[195],"discrimination,":[196],"high":[197],"negative":[198],"predictive":[199],"value":[200],"conservative":[202],"thresholds":[203],"EHR-":[205],"biomarker-based":[207],"triage,":[208],"and,":[209],"some":[211],"studies,":[212],"models":[214],"PDAC":[216],"on":[217],"pre-diagnostic":[218],"CT":[219],"scans,":[220],"providing":[221],"meaningful":[223],"lead":[224],"time":[225],"before":[226],"clinical":[227],"diagnosis.":[228],"These":[229],"findings":[230],"underscore":[231],"but":[234],"also":[235],"need":[237],"prospective,":[239],"pathway-aware":[240],"evaluation.":[241]},"counts_by_year":[],"updated_date":"2026-05-30T06:14:24.967023","created_date":"2026-05-29T00:00:00"}
