{"id":"https://openalex.org/W2990171069","doi":"https://doi.org/10.1136/archdischild-2019-gosh.64","title":"64 Generating synthetic electronic patient records","display_name":"64 Generating synthetic electronic patient records","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W2990171069","doi":"https://doi.org/10.1136/archdischild-2019-gosh.64","mag":"2990171069"},"language":"en","primary_location":{"id":"doi:10.1136/archdischild-2019-gosh.64","doi":"https://doi.org/10.1136/archdischild-2019-gosh.64","is_oa":false,"landing_page_url":"https://doi.org/10.1136/archdischild-2019-gosh.64","pdf_url":null,"source":{"id":"https://openalex.org/S4306500044","display_name":"Abstracts","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Abstracts","raw_type":"proceedings-article"},"volume":null,"type":"conference-abstract","is_traditional":false,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053269279","display_name":"Christopher Tan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2800129641","display_name":"Great Ormond Street Hospital","ror":"https://ror.org/00zn2c847","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I2800129641","https://openalex.org/I2800349819"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Christopher Tan","raw_affiliation_strings":["Great Ormond Street Hospital"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Great Ormond Street Hospital","institution_ids":["https://openalex.org/I2800129641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090095768","display_name":"Huawei Jian","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2800129641","display_name":"Great Ormond Street Hospital","ror":"https://ror.org/00zn2c847","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I2800129641","https://openalex.org/I2800349819"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Huawei Jian","raw_affiliation_strings":["Great Ormond Street Hospital"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Great Ormond Street Hospital","institution_ids":["https://openalex.org/I2800129641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059399086","display_name":"Ben K. Margetts","orcid":"https://orcid.org/0000-0002-6164-0701","observed_orcids":["https://orcid.org/0000-0002-6164-0701"]},"institutions":[{"id":"https://openalex.org/I2800129641","display_name":"Great Ormond Street Hospital","ror":"https://ror.org/00zn2c847","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I2800129641","https://openalex.org/I2800349819"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ben Margetts","raw_affiliation_strings":["Great Ormond Street Hospital"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Great Ormond Street Hospital","institution_ids":["https://openalex.org/I2800129641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2800129641"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"A25.3","last_page":"A26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.30250000953674316,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.30250000953674316,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.2671000063419342,"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/T10350","display_name":"Electronic Health Records Systems","score":0.24300000071525574,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/synthetic-data-generation","display_name":"synthetic data generation","score":0.8379999995231628},{"id":"https://openalex.org/keywords/electronic-health-records","display_name":"electronic health records","score":0.9919999837875366},{"id":"https://openalex.org/keywords/de-identification","display_name":"de-identification","score":0.593999981880188},{"id":"https://openalex.org/keywords/privacy-preserving-data-synthesis","display_name":"privacy-preserving data synthesis","score":0.5730000138282776},{"id":"https://openalex.org/keywords/generative-models","display_name":"generative models","score":0.5849999785423279},{"id":"https://openalex.org/keywords/deep-learning","display_name":"deep learning","score":0.6589999794960022},{"id":"https://openalex.org/keywords/clinical-data-access","display_name":"clinical data access","score":0.5210000276565552},{"id":"https://openalex.org/keywords/disclosure-control","display_name":"disclosure control","score":0.7699999809265137},{"id":"https://openalex.org/keywords/clinical-research-data","display_name":"clinical research data","score":0.4169999957084656}],"concepts":[{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.8471482992172241},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.36904191970825195},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.0781373381614685}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1136/archdischild-2019-gosh.64","doi":"https://doi.org/10.1136/archdischild-2019-gosh.64","is_oa":false,"landing_page_url":"https://doi.org/10.1136/archdischild-2019-gosh.64","pdf_url":null,"source":{"id":"https://openalex.org/S4306500044","display_name":"Abstracts","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Abstracts","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.8048999905586243,"id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7103883647","https://openalex.org/W4406457803","https://openalex.org/W3193469510","https://openalex.org/W4404404817","https://openalex.org/W4402119650","https://openalex.org/W7134828740","https://openalex.org/W3002098238","https://openalex.org/W4385754113","https://openalex.org/W4320342418","https://openalex.org/W4378576258"],"abstract_inverted_index":{"Introduction":[0],"Following":[1],"the":[2,5,22,29,32,35,54,119,130,164,171,224,243,251,271,275,281,297],"publication":[3],"of":[4,21,31,56,124,182,208,226,253],"GOSH":[6,96,154,282],"digital":[7],"strategy,":[8],"electronic":[9],"patient":[10,33,78,140],"record":[11],"(EPR)":[12],"data":[13,27,88,136,148,166,269,277],"has":[14,249],"been":[15],"recognised":[16],"as":[17,274],"an":[18],"ever-growing":[19],"cornerstone":[20],"hospital":[23],"infrastructure.":[24],"Because":[25],"EPR":[26,87,125,135,147,211,256],"remains":[28],"property":[30],"and":[34,80,105,112,121,158,168,174,198,230,296],"NHS,":[36],"access":[37,92],"to":[38,66,72,83,91,108,132,238,262],"it":[39,64],"is":[40],"rightly":[41],"controlled":[42],"by":[43],"stringent":[44,227],"governance":[45],"processes":[46],"which":[47],"introduce":[48],"a":[49,246],"hurdle":[50],"for":[51,81,215],"researchers":[52,82],"requiring":[53],"use":[55,225],"these":[57,60],"data.":[58,126,212,240],"In-short,":[59],"restrictions":[61],"can":[62],"make":[63],"challenging":[65],"run":[67],"short-term":[68],"clinical":[69,276],"research":[70],"projects,":[71],"publish":[73],"reproducible":[74],"results":[75],"without":[76,137],"compromising":[77],"anonymity,":[79],"train":[84],"on":[85,187],"complex":[86],"before":[89],"applying":[90],"it.":[93],"Methods":[94],"The":[95],"DRE":[97,165],"team":[98],"have":[99,129],"worked":[100],"with":[101],"collaborators":[102],"in":[103,270,293],"UCL":[104],"NHS":[106],"Digital":[107,283],"develop":[109],"generative":[110],"statistical":[111,122,228],"deep":[113],"learning":[114],"(AI)":[115],"models":[116,128,184,244],"that":[117,234,258],"learn":[118,176],"structure":[120],"properties":[123],"These":[127],"capability":[131],"generate":[133,267],"synthetic":[134],"reproducing":[138],"individual":[139],"records.":[141],"To":[142],"facilitate":[143],"this":[144],"work,":[145],"de-identified":[146],"from":[149,163],"all":[150],"patients":[151],"treated":[152],"at":[153],"between":[155],"January":[156,159],"2016":[157],"2019":[160],"were":[161,185],"extracted":[162],"lake":[167],"modelled":[169],"using":[170],"PyTorch,":[172],"TensorFlow,":[173],"Scikit":[175],"Python":[177],"libraries.":[178],"Results":[179],"A":[180,213],"range":[181],"privacy-preserving":[183],"developed":[186,222],"admissions,":[188],"ward":[189],"movements,":[190],"demographics,":[191],"drug":[192],"administrations,":[193],"laboratory":[194],"tests,":[195],"vital":[196],"signs,":[197],"microbiological":[199],"isolate":[200],"datasets.":[201],"On":[202],"inspection,":[203],"each":[204,218],"model":[205],"was":[206,221],"capable":[207],"generating":[209],"realistic":[210],"method":[214],"automatically":[216,236],"evaluating":[217],"model\u2019s":[219],"output":[220],"through":[223,280],"similarity":[229],"disclosure":[231],"control":[232],"metrics":[233],"are":[235,259],"applied":[237],"generated":[239],"Discussion":[241],"Integrating":[242],"into":[245],"programmatic":[247],"interface":[248],"enabled":[250],"production":[252],"realistic,":[254],"consistent":[255],"records":[257],"not":[260],"related":[261],"any":[263],"single":[264],"patient,":[265],"yet":[266],"high-quality":[268],"same":[272],"format":[273],"made":[278],"available":[279],"Research":[284],"Environment":[285],"(DRE).":[286],"This":[287],"will":[288],"enable":[289],"future":[290],"data-driven":[291],"developments":[292],"GOSH,":[294],"DRIVE,":[295],"DRE.":[298]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-09-22T06:50:58.402377","created_date":"2019-12-05T00:00:00"}
