{"id":"https://openalex.org/W4319990319","doi":"https://doi.org/10.1109/jbhi.2023.3236822","title":"Glucose Transformer: Forecasting Glucose Level and Events of Hyperglycemia and Hypoglycemia","display_name":"Glucose Transformer: Forecasting Glucose Level and Events of Hyperglycemia and Hypoglycemia","publication_year":2023,"publication_date":"2023-02-02","ids":{"openalex":"https://openalex.org/W4319990319","doi":"https://doi.org/10.1109/jbhi.2023.3236822","pmid":"https://pubmed.ncbi.nlm.nih.gov/37022383"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2023.3236822","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2023.3236822","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Sang-Min Lee","orcid":"https://orcid.org/0000-0003-2469-0352"},"institutions":[{"id":"https://openalex.org/I24541011","display_name":"Soonchunhyang University","ror":"https://ror.org/03qjsrb10","country_code":"KR","type":"education","lineage":["https://openalex.org/I24541011"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Sang-Min Lee","raw_affiliation_strings":["Department of ICT Convergence, Soonchunhyang University, Asan, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-2469-0352","affiliations":[{"raw_affiliation_string":"Department of ICT Convergence, Soonchunhyang University, Asan, South Korea","institution_ids":["https://openalex.org/I24541011"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100644924","display_name":"Dae-Yeon Kim","orcid":"https://orcid.org/0000-0003-1715-2062"},"institutions":[{"id":"https://openalex.org/I24541011","display_name":"Soonchunhyang University","ror":"https://ror.org/03qjsrb10","country_code":"KR","type":"education","lineage":["https://openalex.org/I24541011"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dae-Yeon Kim","raw_affiliation_strings":["Department of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-1715-2062","affiliations":[{"raw_affiliation_string":"Department of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan, South Korea","institution_ids":["https://openalex.org/I24541011"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027662394","display_name":"Jiyoung Woo","orcid":"https://orcid.org/0000-0001-8231-0018"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]},{"id":"https://openalex.org/I24541011","display_name":"Soonchunhyang University","ror":"https://ror.org/03qjsrb10","country_code":"KR","type":"education","lineage":["https://openalex.org/I24541011"]}],"countries":["KR","US"],"is_corresponding":false,"raw_author_name":"Jiyoung Woo","raw_affiliation_strings":["Department of Big Data Engineering, Soonchunhyang University, Asan, South Korea","Management Information System Department of Arizona University, Tucson, AZ, USA"],"raw_orcid":"https://orcid.org/0000-0001-8231-0018","affiliations":[{"raw_affiliation_string":"Department of Big Data Engineering, Soonchunhyang University, Asan, South Korea","institution_ids":["https://openalex.org/I24541011"]},{"raw_affiliation_string":"Management Information System Department of Arizona University, Tucson, AZ, USA","institution_ids":["https://openalex.org/I138006243"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24541011"],"apc_list":null,"apc_paid":null,"fwci":9.488,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":{"value":0.98538866,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"27","issue":"3","first_page":"1600","last_page":"1611"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10560","display_name":"Diabetes Management and Research","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"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/T10560","display_name":"Diabetes Management and Research","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"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/T10027","display_name":"Diabetes, Cardiovascular Risks, and Lipoproteins","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9855999946594238,"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/hypoglycemia","display_name":"Hypoglycemia","score":0.7922332882881165},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5874127745628357},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5758165121078491},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5540237426757812},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46690279245376587},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43759772181510925},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"Diabetes mellitus","score":0.4212700128555298},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3313329219818115},{"id":"https://openalex.org/keywords/endocrinology","display_name":"Endocrinology","score":0.2291652262210846},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0936184823513031}],"concepts":[{"id":"https://openalex.org/C2780668416","wikidata":"https://www.wikidata.org/wiki/Q202758","display_name":"Hypoglycemia","level":3,"score":0.7922332882881165},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5874127745628357},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5758165121078491},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5540237426757812},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46690279245376587},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43759772181510925},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.4212700128555298},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3313329219818115},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.2291652262210846},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0936184823513031},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jbhi.2023.3236822","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2023.3236822","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},{"id":"pmid:37022383","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37022383","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":"IEEE journal of biomedical and health informatics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1531333757","https://openalex.org/W1902237438","https://openalex.org/W2064675550","https://openalex.org/W2105482032","https://openalex.org/W2150355110","https://openalex.org/W2161212365","https://openalex.org/W2194775991","https://openalex.org/W2589083807","https://openalex.org/W2767690062","https://openalex.org/W2943118732","https://openalex.org/W2963123914","https://openalex.org/W2968714441","https://openalex.org/W2988860641","https://openalex.org/W3012064747","https://openalex.org/W3016173377","https://openalex.org/W3040704051","https://openalex.org/W3097099548","https://openalex.org/W3100358445","https://openalex.org/W3100777112","https://openalex.org/W3135438941","https://openalex.org/W3178109510","https://openalex.org/W3183804512","https://openalex.org/W4200358162","https://openalex.org/W4200610982","https://openalex.org/W4210566137","https://openalex.org/W4210792026","https://openalex.org/W4213092833","https://openalex.org/W4220952380","https://openalex.org/W4225740406","https://openalex.org/W4288104102","https://openalex.org/W4294583247","https://openalex.org/W4298289240","https://openalex.org/W4385245566","https://openalex.org/W6637568146","https://openalex.org/W6640212811","https://openalex.org/W6679436768","https://openalex.org/W6684191040","https://openalex.org/W6688325169","https://openalex.org/W6738960736","https://openalex.org/W6743485176","https://openalex.org/W6767669220","https://openalex.org/W6767782324","https://openalex.org/W6780226713","https://openalex.org/W6784018277","https://openalex.org/W6784333009","https://openalex.org/W6910546390","https://openalex.org/W6986594840"],"related_works":["https://openalex.org/W4213318607","https://openalex.org/W2373648995","https://openalex.org/W4361214851","https://openalex.org/W2084374993","https://openalex.org/W2743557138","https://openalex.org/W4312224640","https://openalex.org/W2733743115","https://openalex.org/W2309375030","https://openalex.org/W2469549964","https://openalex.org/W4380075502"],"abstract_inverted_index":{"To":[0],"avoid":[1],"the":[2,57,67,82,107,125,134,151,158,174,184,210],"adverse":[3],"consequences":[4],"from":[5,21,46],"abrupt":[6],"increases":[7],"in":[8,62,78,85,106,121,124],"blood":[9,18,35,68],"glucose,":[10],"diabetic":[11,199],"inpatients":[12,47,200],"should":[13],"be":[14],"closely":[15],"monitored.":[16],"Using":[17],"glucose":[19,36,41,69],"data":[20,44,130,170,181,185,195],"type":[22,49,197],"2":[23,50,198],"diabetes":[24,51],"patients,":[25],"we":[26,144,167,193,204],"propose":[27],"a":[28,53,89,97,129,146,163,169],"deep":[29,147],"learning":[30,148,207],"model-based":[31],"framework":[32,149],"to":[33,65,87,100,156,182,189,208],"forecast":[34,66],"levels.":[37],"We":[38,55,80,127],"used":[39,61],"continuous":[40],"monitoring":[42],"(CGM)":[43],"collected":[45,194],"with":[48],"for":[52,179,196,201],"week.":[54],"adopted":[56,168],"Transformer":[58,86,103,155],"model,":[59],"commonly":[60],"sequence":[63],"data,":[64],"level":[70],"over":[71],"time":[72],"and":[73,76,93,95,109,114,118,160,188,214],"detect":[74],"hyperglycemia":[75,92],"hypoglycemia":[77,115],"advance.":[79],"expected":[81],"attention":[83],"mechanism":[84],"reveal":[88],"hint":[90],"of":[91,111,154,212],"hypoglycemia,":[94],"performed":[96],"comparative":[98],"study":[99],"determine":[101],"whether":[102],"was":[104],"effective":[105],"classification":[108,161],"regression":[110,159,213],"glucose.":[112],"Hyperglycemia":[113],"rarely":[116],"occur":[117],"this":[119],"results":[120],"an":[122],"imbalance":[123,186],"classification.":[126,215],"built":[128],"augmentation":[131,171],"model":[132,172],"using":[133,173],"generative":[135,175],"adversarial":[136,176],"network.":[137],"Our":[138],"contributions":[139],"are":[140],"as":[141],"follows.":[142],"First,":[143],"developed":[145],"utilizing":[150],"encoder":[152],"part":[153],"perform":[157],"under":[162],"unified":[164],"framework.":[165],"Second,":[166],"network":[177],"suitable":[178],"time-series":[180],"solve":[183],"problem":[187],"improve":[190,209],"performance.":[191],"Third,":[192],"mid-time.":[202],"Finally,":[203],"incorporated":[205],"transfer":[206],"performance":[211]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":3}],"updated_date":"2026-05-08T15:41:06.802602","created_date":"2025-10-10T00:00:00"}
