{"id":"https://openalex.org/W2947919073","doi":"https://doi.org/10.1109/access.2019.2919184","title":"A Multi-Patient Data-Driven Approach to Blood Glucose Prediction","display_name":"A Multi-Patient Data-Driven Approach to Blood Glucose Prediction","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2947919073","doi":"https://doi.org/10.1109/access.2019.2919184","mag":"2947919073"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2919184","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2919184","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08723121.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08723121.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046819248","display_name":"Alessandro Aliberti","orcid":"https://orcid.org/0000-0001-8828-608X"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Alessandro Aliberti","raw_affiliation_strings":["Department of Control and Computer Engineering, Politecnico di Torino, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Control and Computer Engineering, Politecnico di Torino, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038168363","display_name":"Irene Pupillo","orcid":null},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Irene Pupillo","raw_affiliation_strings":["Department of Control and Computer Engineering, Politecnico di Torino, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Control and Computer Engineering, Politecnico di Torino, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029633909","display_name":"Stefano Terna","orcid":"https://orcid.org/0000-0003-2696-6076"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stefano Terna","raw_affiliation_strings":["TomorrowData, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"TomorrowData, Turin, Italy","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005432629","display_name":"Enrico Macii","orcid":"https://orcid.org/0000-0001-9046-5618"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Enrico Macii","raw_affiliation_strings":["Interuniversity Department of Regional and Urban Studies and Planning, Politecnico di Torino, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"Interuniversity Department of Regional and Urban Studies and Planning, Politecnico di Torino, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028610334","display_name":"Santa Di Cataldo","orcid":"https://orcid.org/0000-0002-6239-8945"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Santa Di Cataldo","raw_affiliation_strings":["Department of Control and Computer Engineering, Politecnico di Torino, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Control and Computer Engineering, Politecnico di Torino, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049181393","display_name":"Edoardo Patti","orcid":"https://orcid.org/0000-0002-6043-6477"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Edoardo Patti","raw_affiliation_strings":["Department of Control and Computer Engineering, Politecnico di Torino, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Control and Computer Engineering, Politecnico di Torino, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031653904","display_name":"Andrea Acquaviva","orcid":null},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Andrea Acquaviva","raw_affiliation_strings":["Interuniversity Department of Regional and Urban Studies and Planning, Politecnico di Torino, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"Interuniversity Department of Regional and Urban Studies and Planning, Politecnico di Torino, Turin, Italy","institution_ids":["https://openalex.org/I177477856"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5046819248"],"corresponding_institution_ids":["https://openalex.org/I177477856"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":9.4047,"has_fulltext":true,"cited_by_count":133,"citation_normalized_percentile":{"value":0.98666,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"7","issue":null,"first_page":"69311","last_page":"69325"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10560","display_name":"Diabetes Management and Research","score":0.9998999834060669,"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":0.9998999834060669,"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/T11623","display_name":"Hyperglycemia and glycemic control in critically ill and hospitalized patients","score":0.9933000206947327,"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/T11171","display_name":"Diabetes and associated disorders","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.7356932163238525},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6710566282272339},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6640215516090393},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6046984791755676},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5987572073936462},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5376805663108826},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5072557330131531},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.44705572724342346},{"id":"https://openalex.org/keywords/continuous-glucose-monitoring","display_name":"Continuous glucose monitoring","score":0.4399748146533966},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.43030399084091187},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21960577368736267},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"Diabetes mellitus","score":0.2080424726009369},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14742159843444824},{"id":"https://openalex.org/keywords/type-1-diabetes","display_name":"Type 1 diabetes","score":0.14673417806625366},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.14254048466682434}],"concepts":[{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7356932163238525},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6710566282272339},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6640215516090393},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6046984791755676},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5987572073936462},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5376805663108826},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5072557330131531},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.44705572724342346},{"id":"https://openalex.org/C2986379492","wikidata":"https://www.wikidata.org/wiki/Q1638492","display_name":"Continuous glucose monitoring","level":4,"score":0.4399748146533966},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.43030399084091187},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21960577368736267},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.2080424726009369},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14742159843444824},{"id":"https://openalex.org/C2781232474","wikidata":"https://www.wikidata.org/wiki/Q124407","display_name":"Type 1 diabetes","level":3,"score":0.14673417806625366},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.14254048466682434},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2919184","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2919184","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08723121.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:eefdf6bd91fa430ea2be08fc89fa736a","is_oa":true,"landing_page_url":"https://doaj.org/article/eefdf6bd91fa430ea2be08fc89fa736a","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 69311-69325 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2919184","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2919184","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08723121.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.44999998807907104,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320313985","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2947919073.pdf","grobid_xml":"https://content.openalex.org/works/W2947919073.grobid-xml"},"referenced_works_count":74,"referenced_works":["https://openalex.org/W36455107","https://openalex.org/W191220328","https://openalex.org/W200033674","https://openalex.org/W354722939","https://openalex.org/W581956982","https://openalex.org/W1522301498","https://openalex.org/W1535260033","https://openalex.org/W1608151369","https://openalex.org/W1689711448","https://openalex.org/W1815076433","https://openalex.org/W1855258198","https://openalex.org/W1887189770","https://openalex.org/W1964947170","https://openalex.org/W1988587963","https://openalex.org/W2014887370","https://openalex.org/W2018471296","https://openalex.org/W2019652008","https://openalex.org/W2028072219","https://openalex.org/W2031534975","https://openalex.org/W2038343656","https://openalex.org/W2046853583","https://openalex.org/W2058101613","https://openalex.org/W2062573090","https://openalex.org/W2064675550","https://openalex.org/W2096170052","https://openalex.org/W2101539208","https://openalex.org/W2111369274","https://openalex.org/W2111406701","https://openalex.org/W2116261113","https://openalex.org/W2124918510","https://openalex.org/W2126105335","https://openalex.org/W2129995532","https://openalex.org/W2132115169","https://openalex.org/W2132228725","https://openalex.org/W2133380412","https://openalex.org/W2134295053","https://openalex.org/W2136848157","https://openalex.org/W2140064412","https://openalex.org/W2158711921","https://openalex.org/W2168087114","https://openalex.org/W2213612645","https://openalex.org/W2218089048","https://openalex.org/W2278129565","https://openalex.org/W2523526638","https://openalex.org/W2529767183","https://openalex.org/W2551626608","https://openalex.org/W2606106417","https://openalex.org/W2736066352","https://openalex.org/W2743945814","https://openalex.org/W2793729473","https://openalex.org/W2810149880","https://openalex.org/W2884370030","https://openalex.org/W2888578485","https://openalex.org/W2889249519","https://openalex.org/W2890390797","https://openalex.org/W2891629281","https://openalex.org/W2963123914","https://openalex.org/W2963452728","https://openalex.org/W2963922828","https://openalex.org/W2964121744","https://openalex.org/W3104876936","https://openalex.org/W4211058450","https://openalex.org/W4240691156","https://openalex.org/W4241883936","https://openalex.org/W4254218124","https://openalex.org/W4299838440","https://openalex.org/W6616837769","https://openalex.org/W6631190155","https://openalex.org/W6638545294","https://openalex.org/W6688281636","https://openalex.org/W6738957339","https://openalex.org/W6742632731","https://openalex.org/W6753749718","https://openalex.org/W6754138717"],"related_works":["https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W3032952384","https://openalex.org/W3034302643","https://openalex.org/W1847088711","https://openalex.org/W4225394202","https://openalex.org/W3036642985","https://openalex.org/W2050540762","https://openalex.org/W2349019353","https://openalex.org/W2154965898"],"abstract_inverted_index":{"Continuous":[0],"glucose":[1,101,235],"monitoring":[2],"systems":[3],"(CGMSs)":[4],"allow":[5],"measuring":[6],"the":[7,41,45,58,63,66,73,77,86,89,96,186,203,222,230,233],"blood":[8],"glycaemic":[9,42],"value":[10],"of":[11,24,40,48,57,62,76,88,103,109,135,227,240],"a":[12,16,21,69,104,120],"diabetic":[13,59],"patient":[14],"at":[15],"high":[17],"sampling":[18],"rate,":[19],"producing":[20],"considerable":[22],"amount":[23],"data.":[25],"These":[26,161],"data":[27],"can":[28],"be":[29],"effectively":[30],"used":[31],"by":[32],"machine":[33],"learning":[34],"techniques":[35],"to":[36,114],"infer":[37,115],"future":[38,116],"values":[39,118],"concentration,":[43],"allowing":[44],"early":[46],"prevention":[47],"dangerous":[49],"hyperglycaemic":[50],"or":[51],"hypoglycaemic":[52],"states":[53],"and":[54,84,106,111,130,154,180,212,218,232,237],"better":[55],"optimization":[56],"treatment.":[60],"Most":[61],"approaches":[64],"in":[65,141,225,238],"literature":[67,168],"learn":[68],"prediction":[70,97,144,190,198],"model":[71],"from":[72],"past":[74],"samples":[75],"same":[78],"patient,":[79],"which":[80],"needs":[81],"extensive":[82],"calibrations":[83],"limits":[85],"usability":[87],"system.":[90],"In":[91],"this":[92,126],"paper,":[93],"we":[94,128],"investigate":[95],"models":[98],"trained":[99],"on":[100,119,148,155,172],"signals":[102],"large":[105],"heterogeneous":[107],"cohort":[108],"patients":[110],"then":[112],"applied":[113],"glucose-level":[117,214],"completely":[121],"new":[122],"patient.":[123],"To":[124],"achieve":[125],"purpose,":[127],"designed":[129],"compared":[131,165],"two":[132],"different":[133],"types":[134],"solutions":[136,162],"that":[137],"were":[138,163],"proved":[139],"successful":[140],"many":[142],"time-series":[143],"problems":[145],"based":[146,171],"respectively,":[147,170],"non-linear":[149],"autoregressive":[150,177],"(NAR)":[151],"neural":[152,174,182],"network":[153],"long":[156],"short-term":[157,194],"memory":[158],"(LSTM)":[159],"networks.":[160],"experimentally":[164],"with":[166,197],"three":[167],"approaches,":[169],"feed-forward":[173],"networks":[175,183],"(FNNs),":[176],"(AR)":[178],"models,":[179],"recurrent":[181],"(RNN).":[184],"While":[185],"NAR":[187],"obtained":[188,205],"good":[189,207],"accuracy":[191],"only":[192],"for":[193,210],"predictions":[195],"(i.e.,":[196],"horizon":[199],"within":[200],"30":[201],"min),":[202],"LSTM":[204],"extremely":[206],"performance":[208],"both":[209],"short-":[211],"long-term":[213],"inference":[215],"(60":[216],"min":[217],"more),":[219],"overcoming":[220],"all":[221],"other":[223],"methods":[224],"terms":[226,239],"correlation":[228],"between":[229],"measured":[231],"predicted":[234],"signal":[236],"clinical":[241],"outcome.":[242]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":30},{"year":2023,"cited_by_count":27},{"year":2022,"cited_by_count":23},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":3}],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}