{"id":"https://openalex.org/W2921914364","doi":"https://doi.org/10.3390/s19051181","title":"SynSys: A Synthetic Data Generation System for Healthcare Applications","display_name":"SynSys: A Synthetic Data Generation System for Healthcare Applications","publication_year":2019,"publication_date":"2019-03-08","ids":{"openalex":"https://openalex.org/W2921914364","doi":"https://doi.org/10.3390/s19051181","mag":"2921914364","pmid":"https://pubmed.ncbi.nlm.nih.gov/30857130"},"language":"en","primary_location":{"id":"doi:10.3390/s19051181","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19051181","pdf_url":"https://www.mdpi.com/1424-8220/19/5/1181/pdf?version=1552031102","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/19/5/1181/pdf?version=1552031102","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087418745","display_name":"Jessamyn Dahmen","orcid":null},"institutions":[{"id":"https://openalex.org/I72951846","display_name":"Washington State University","ror":"https://ror.org/05dk0ce17","country_code":"US","type":"education","lineage":["https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jessamyn Dahmen","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164, USA","institution_ids":["https://openalex.org/I72951846"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048183050","display_name":"Diane J. Cook","orcid":"https://orcid.org/0000-0002-4441-7508"},"institutions":[{"id":"https://openalex.org/I72951846","display_name":"Washington State University","ror":"https://ror.org/05dk0ce17","country_code":"US","type":"education","lineage":["https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Diane Cook","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164, USA"],"raw_orcid":"https://orcid.org/0000-0002-4441-7508","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164, USA","institution_ids":["https://openalex.org/I72951846"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5048183050"],"corresponding_institution_ids":["https://openalex.org/I72951846"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":9.1327,"has_fulltext":true,"cited_by_count":176,"citation_normalized_percentile":{"value":0.98550725,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"19","issue":"5","first_page":"1181","last_page":"1181"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9975000023841858,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9911999702453613,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.7683480978012085},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7633339166641235},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5559115409851074},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5348291397094727},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5012457370758057},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4982180595397949},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.48962002992630005},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4159565567970276},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.08044251799583435}],"concepts":[{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.7683480978012085},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7633339166641235},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5559115409851074},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5348291397094727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5012457370758057},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4982180595397949},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.48962002992630005},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4159565567970276},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.08044251799583435}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003695","descriptor_name":"Delivery of Health Care","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D003695","descriptor_name":"Delivery of Health Care","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D003695","descriptor_name":"Delivery of Health Care","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008390","descriptor_name":"Markov Chains","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.3390/s19051181","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19051181","pdf_url":"https://www.mdpi.com/1424-8220/19/5/1181/pdf?version=1552031102","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:30857130","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30857130","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:da636e3a7d5f4334bf8e9a2773e2daf0","is_oa":true,"landing_page_url":"https://doaj.org/article/da636e3a7d5f4334bf8e9a2773e2daf0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 19, Iss 5, p 1181 (2019)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:5445372","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6427177","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:mdpi.com:/1424-8220/19/5/1181/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/s19051181","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s19051181","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19051181","pdf_url":"https://www.mdpi.com/1424-8220/19/5/1181/pdf?version=1552031102","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1229512862","display_name":null,"funder_award_id":"R01 EB009675","funder_id":"https://openalex.org/F4320337363","funder_display_name":"National Institute of Biomedical Imaging and Bioengineering"},{"id":"https://openalex.org/G154243151","display_name":null,"funder_award_id":"R25 AG046114","funder_id":"https://openalex.org/F4320337337","funder_display_name":"National Institute on Aging"},{"id":"https://openalex.org/G1590387639","display_name":null,"funder_award_id":"R01 NR016732","funder_id":"https://openalex.org/F4320337353","funder_display_name":"National Institute of Nursing Research"},{"id":"https://openalex.org/G1682206514","display_name":null,"funder_award_id":"R01 EB015853","funder_id":"https://openalex.org/F4320337363","funder_display_name":"National Institute of Biomedical Imaging and Bioengineering"},{"id":"https://openalex.org/G4250402350","display_name":null,"funder_award_id":"121407","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7448846450","display_name":null,"funder_award_id":"R25 EB024327","funder_id":"https://openalex.org/F4320337363","funder_display_name":"National Institute of Biomedical Imaging and Bioengineering"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337337","display_name":"National Institute on Aging","ror":"https://ror.org/049v75w11"},{"id":"https://openalex.org/F4320337353","display_name":"National Institute of Nursing Research","ror":"https://ror.org/01y3zfr79"},{"id":"https://openalex.org/F4320337363","display_name":"National Institute of Biomedical Imaging and Bioengineering","ror":"https://ror.org/00372qc85"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2921914364.pdf","grobid_xml":"https://content.openalex.org/works/W2921914364.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1839219472","https://openalex.org/W2015200434","https://openalex.org/W2020605840","https://openalex.org/W2099471712","https://openalex.org/W2132174073","https://openalex.org/W2135090840","https://openalex.org/W2144340284","https://openalex.org/W2581465409","https://openalex.org/W2652015611","https://openalex.org/W2700341059","https://openalex.org/W2773662615","https://openalex.org/W2789701916","https://openalex.org/W2792071264","https://openalex.org/W2805066180","https://openalex.org/W2891240256","https://openalex.org/W2963942586","https://openalex.org/W2964317695","https://openalex.org/W6732321957"],"related_works":["https://openalex.org/W2053269318","https://openalex.org/W3035069238","https://openalex.org/W3182611934","https://openalex.org/W2514264328","https://openalex.org/W1969032534","https://openalex.org/W4388067754","https://openalex.org/W3109499659","https://openalex.org/W4382315317","https://openalex.org/W2966641257","https://openalex.org/W4399530423"],"abstract_inverted_index":{"Creation":[0],"of":[1,11,20,33,65,127,155,163,189],"realistic":[2,108,123],"synthetic":[3,26,43,58,85,148],"behavior-based":[4],"sensor":[5],"data":[6,27,44,61,86,111,116,124,132,134,139,149,157,166,191],"is":[7,63,112,167,176],"an":[8],"important":[9],"aspect":[10],"testing":[12],"machine":[13,41],"learning":[14,171],"techniques":[15],"for":[16,24],"healthcare":[17],"applications.":[18],"Many":[19],"the":[21,109,153,186],"existing":[22],"approaches":[23],"generating":[25,156],"are":[28,76],"often":[29],"limited":[30],"in":[31,125],"terms":[32,126],"complexity":[34],"and":[35,72,117,138],"realism.":[36],"We":[37,52,82,96],"introduce":[38],"SynSys,":[39],"a":[40,90,103,160],"learning-based":[42],"generation":[45,87,150],"method,":[46],"to":[47,56,105,114,130,152,178,184],"improve":[48,179],"upon":[49],"these":[50],"limitations.":[51],"use":[53,97],"this":[54],"method":[55],"generate":[57],"time":[59,98,142],"series":[60,99],"that":[62,119,174],"composed":[64],"nested":[66],"sequences":[67],"using":[68,185],"hidden":[69],"Markov":[70],"models":[71,74],"regression":[73],"which":[75],"initially":[77],"trained":[78],"on":[79,89],"real":[80,91,115,190],"datasets.":[81],"test":[83],"our":[84,147],"technique":[88,151],"annotated":[92],"smart":[93],"home":[94],"dataset.":[95],"distance":[100,128],"measures":[101],"as":[102],"baseline":[104],"determine":[106],"how":[107],"generated":[110],"compared":[113,129,183],"demonstrate":[118,173],"SynSys":[120,175],"produces":[121],"more":[122],"random":[131],"generation,":[133],"from":[135,140],"another":[136,141],"home,":[137],"period.":[143],"Finally,":[144],"we":[145,172],"apply":[146],"problem":[154],"when":[158],"only":[159],"small":[161,187],"amount":[162,188],"ground":[164],"truth":[165],"available.":[168],"Using":[169],"semi-supervised":[170],"able":[177],"activity":[180],"recognition":[181],"accuracy":[182],"alone.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":34},{"year":2024,"cited_by_count":34},{"year":2023,"cited_by_count":39},{"year":2022,"cited_by_count":26},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":4}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}