{"id":"https://openalex.org/W7127318314","doi":"https://doi.org/10.48550/arxiv.2602.01086","title":"MedBeads: An AI-Native Clinical Context Graph Built from Immutable Beads and Reconstructable Clinical Links","display_name":"MedBeads: An AI-Native Clinical Context Graph Built from Immutable Beads and Reconstructable Clinical Links","publication_year":2026,"publication_date":"2026-02-01","ids":{"openalex":"https://openalex.org/W7127318314","doi":"https://doi.org/10.48550/arxiv.2602.01086"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.01086","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.01086","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2602.01086","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124904501","display_name":"Takahito Nakajima","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Nakajima, Takahito","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5124904501"],"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":0.3070000112056732,"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":0.3070000112056732,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.2451999932527542,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/T11986","display_name":"Scientific Computing and Data Management","score":0.0406000018119812,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.5968999862670898},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.5889999866485596},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5658000111579895},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5062999725341797},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.44850000739097595},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.4153999984264374},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.36649999022483826},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.35850000381469727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7943000197410583},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.5968999862670898},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.5889999866485596},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5658000111579895},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5062999725341797},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.45680001378059387},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.44850000739097595},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.4153999984264374},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3880999982357025},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.36649999022483826},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.35850000381469727},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.35109999775886536},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.34389999508857727},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.3434999883174896},{"id":"https://openalex.org/C2781020372","wikidata":"https://www.wikidata.org/wiki/Q533093","display_name":"On the fly","level":2,"score":0.3400000035762787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.328000009059906},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.3208000063896179},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C47487241","wikidata":"https://www.wikidata.org/wiki/Q5227230","display_name":"Data access","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C4379982","wikidata":"https://www.wikidata.org/wiki/Q1273511","display_name":"Software visualization","level":5,"score":0.2842999994754791},{"id":"https://openalex.org/C185578843","wikidata":"https://www.wikidata.org/wiki/Q10609775","display_name":"Information visualization","level":3,"score":0.2838999927043915},{"id":"https://openalex.org/C16311509","wikidata":"https://www.wikidata.org/wiki/Q4148050","display_name":"Dependency graph","level":3,"score":0.2793999910354614},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2696000039577484},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.26840001344680786},{"id":"https://openalex.org/C149091818","wikidata":"https://www.wikidata.org/wiki/Q2429814","display_name":"Software system","level":3,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.01086","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.01086","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.01086","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.01086","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6314572095870972}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Generative":[0],"AI":[1],"can":[2,47,132],"encode":[3],"substantial":[4],"medical":[5],"knowledge,":[6],"but":[7,28,51],"patient-specific":[8],"answers":[9],"remain":[10],"constrained":[11],"by":[12,32,93,212],"the":[13,35],"context":[14,40],"supplied":[15],"at":[16],"inference":[17],"time.":[18],"Electronic":[19],"health":[20],"records":[21,59],"and":[22,26,38,98,146,151,153,166,183,188,196],"FHIR":[23,176],"support":[24],"documentation":[25],"interoperability,":[27],"they":[29,131],"do":[30],"not":[31,198],"themselves":[33],"define":[34],"complete,":[36],"current,":[37],"auditable":[39],"a":[41,74,105,112,120,209,214],"model":[42],"should":[43],"receive.":[44],"Similarity-based":[45],"retrieval":[46],"find":[48],"related":[49],"text,":[50],"it":[52],"neither":[53],"guarantees":[54],"collection":[55],"of":[56,77,172,224],"clinically":[57],"connected":[58],"nor":[60],"makes":[61],"omissions":[62],"explicit.":[63],"We":[64],"introduce":[65],"MedBeads,":[66],"an":[67,86,101,221],"AI-facing":[68],"clinical":[69,88,117,140,147,203,217],"record":[70],"substrate":[71],"that":[72],"assembles":[73],"declared":[75],"closure":[76],"longitudinal":[78],"patient":[79],"information":[80],"before":[81],"generation.":[82],"A":[83],"Bead":[84],"is":[85],"immutable":[87],"or":[89,156,201],"knowledge":[90,129,136],"object":[91],"identified":[92],"SHA-256":[94],"over":[95],"canonical":[96],"content":[97],"stored":[99],"as":[100,208],"append-only":[102,164],"frame":[103],"in":[104],"patient-scoped":[106],"Pod.":[107],"Structural":[108],"parent":[109],"edges":[110],"form":[111],"patient-rooted":[113],"Merkle":[114],"DAG.":[115],"Typed":[116],"links":[118],"occupy":[119],"separate,":[121],"reconstructable":[122,167],"interpretation":[123],"layer":[124],"derived":[125],"from":[126],"signed,":[127],"versioned":[128],"rules;":[130],"be":[133],"recomputed":[134],"when":[135],"changes":[137],"without":[138],"rewriting":[139],"facts.":[141],"Retrieval":[142],"follows":[143],"authorized":[144],"structural":[145],"edges,":[148],"resolves":[149],"amendments":[150],"retractions,":[152],"reports":[154],"policy":[155],"token":[157],"truncation.":[158],"An":[159],"open-source":[160],"Go":[161],"implementation":[162],"uses":[163],"Pods":[165],"SQLite":[168],"projections.":[169],"File-based":[170],"conversion":[171],"1,135":[173],"synthetic":[174],"Synthea":[175],"bundles":[177],"produced":[178],"approximately":[179],"one":[180],"million":[181],"Beads":[182],"demonstrated":[184],"deterministic":[185],"clinical-link":[186],"derivation":[187],"interpretation-layer":[189],"reconstruction.":[190],"These":[191],"engineering":[192],"results":[193],"establish":[194],"feasibility":[195],"reproducibility,":[197],"reduced":[199],"hallucination":[200],"improved":[202],"outcomes.":[204],"MedBeads":[205],"reframes":[206],"grounding":[207],"data-structure":[210],"problem":[211],"delivering":[213],"policy-bounded,":[215],"provenance-bearing":[216],"subgraph":[218],"rather":[219],"than":[220],"opaque":[222],"list":[223],"similar":[225],"fragments.":[226]},"counts_by_year":[],"updated_date":"2026-08-16T07:02:28.622633","created_date":"2026-02-04T00:00:00"}