{"id":"https://openalex.org/W3045323379","doi":"https://doi.org/10.1109/iccicc46617.2019.9146049","title":"Early Experience in Forecasting Blood Glucose Levels Using a Delayed and Auto-Regressive Jump Neural Network","display_name":"Early Experience in Forecasting Blood Glucose Levels Using a Delayed and Auto-Regressive Jump Neural Network","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W3045323379","doi":"https://doi.org/10.1109/iccicc46617.2019.9146049","mag":"3045323379"},"language":"en","primary_location":{"id":"doi:10.1109/iccicc46617.2019.9146049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccicc46617.2019.9146049","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 18th International Conference on Cognitive Informatics &amp; Cognitive Computing (ICCI*CC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5065762176","display_name":"Federico D\u2019Antoni","orcid":"https://orcid.org/0000-0001-7377-5462"},"institutions":[{"id":"https://openalex.org/I155125353","display_name":"Universit\u00e0 Campus Bio-Medico","ror":"https://ror.org/04gqx4x78","country_code":"IT","type":"education","lineage":["https://openalex.org/I155125353"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Federico D'Antoni","raw_affiliation_strings":["Department of Engineering, Unit of Computer Systems and Bioinformatics, Universit\u00e0 Campus Bio-Medico di Roma, Rome, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering, Unit of Computer Systems and Bioinformatics, Universit\u00e0 Campus Bio-Medico di Roma, Rome, Italy","institution_ids":["https://openalex.org/I155125353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062985886","display_name":"Mario Merone","orcid":"https://orcid.org/0000-0002-9406-2397"},"institutions":[{"id":"https://openalex.org/I155125353","display_name":"Universit\u00e0 Campus Bio-Medico","ror":"https://ror.org/04gqx4x78","country_code":"IT","type":"education","lineage":["https://openalex.org/I155125353"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Mario Merone","raw_affiliation_strings":["Department of Engineering, Unit of Computer Systems and Bioinformatics, Universit\u00e0 Campus Bio-Medico di Roma, Rome, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering, Unit of Computer Systems and Bioinformatics, Universit\u00e0 Campus Bio-Medico di Roma, Rome, Italy","institution_ids":["https://openalex.org/I155125353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082371656","display_name":"Vincenzo Piemonte","orcid":"https://orcid.org/0000-0002-2421-3938"},"institutions":[{"id":"https://openalex.org/I155125353","display_name":"Universit\u00e0 Campus Bio-Medico","ror":"https://ror.org/04gqx4x78","country_code":"IT","type":"education","lineage":["https://openalex.org/I155125353"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Vincenzo Piemonte","raw_affiliation_strings":["Department of Engineering, Unit of Chemical Engineering, Universit\u00e0 Campus Bio-Medico di Roma, Rome, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering, Unit of Chemical Engineering, Universit\u00e0 Campus Bio-Medico di Roma, Rome, Italy","institution_ids":["https://openalex.org/I155125353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087265840","display_name":"Paolo Pozzilli","orcid":"https://orcid.org/0000-0001-5090-636X"},"institutions":[{"id":"https://openalex.org/I155125353","display_name":"Universit\u00e0 Campus Bio-Medico","ror":"https://ror.org/04gqx4x78","country_code":"IT","type":"education","lineage":["https://openalex.org/I155125353"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Pozzilli","raw_affiliation_strings":["Unit of Diabetology and Endocrinology, Department of Medicine, Universit\u00e0 Campus Bio-Medico di Roma, Rome, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Unit of Diabetology and Endocrinology, Department of Medicine, Universit\u00e0 Campus Bio-Medico di Roma, Rome, Italy","institution_ids":["https://openalex.org/I155125353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084631519","display_name":"Giulio Iannello","orcid":"https://orcid.org/0000-0003-3864-5800"},"institutions":[{"id":"https://openalex.org/I155125353","display_name":"Universit\u00e0 Campus Bio-Medico","ror":"https://ror.org/04gqx4x78","country_code":"IT","type":"education","lineage":["https://openalex.org/I155125353"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giulio Iannello","raw_affiliation_strings":["Department of Engineering, Unit of Computer Systems and Bioinformatics, Universit\u00e0 Campus Bio-Medico di Roma, Rome, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering, Unit of Computer Systems and Bioinformatics, Universit\u00e0 Campus Bio-Medico di Roma, Rome, Italy","institution_ids":["https://openalex.org/I155125353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003216983","display_name":"Paolo Soda","orcid":"https://orcid.org/0000-0003-2621-072X"},"institutions":[{"id":"https://openalex.org/I155125353","display_name":"Universit\u00e0 Campus Bio-Medico","ror":"https://ror.org/04gqx4x78","country_code":"IT","type":"education","lineage":["https://openalex.org/I155125353"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Soda","raw_affiliation_strings":["Department of Engineering, Unit of Computer Systems and Bioinformatics, Universit\u00e0 Campus Bio-Medico di Roma, Rome, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering, Unit of Computer Systems and Bioinformatics, Universit\u00e0 Campus Bio-Medico di Roma, Rome, Italy","institution_ids":["https://openalex.org/I155125353"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I155125353"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"394","last_page":"402"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10560","display_name":"Diabetes Management and Research","score":0.9947999715805054,"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":0.9947999715805054,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.984000027179718,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9835000038146973,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7283437252044678},{"id":"https://openalex.org/keywords/jump","display_name":"Jump","score":0.6476502418518066},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6177261471748352},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.5283390283584595},{"id":"https://openalex.org/keywords/continuous-glucose-monitoring","display_name":"Continuous glucose monitoring","score":0.46212005615234375},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.42537280917167664},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4167099595069885},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41232264041900635},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3672561049461365},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"Diabetes mellitus","score":0.35943639278411865},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2655814588069916},{"id":"https://openalex.org/keywords/type-1-diabetes","display_name":"Type 1 diabetes","score":0.20088785886764526},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.19804871082305908},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1353083848953247},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1261291801929474},{"id":"https://openalex.org/keywords/endocrinology","display_name":"Endocrinology","score":0.08756858110427856}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7283437252044678},{"id":"https://openalex.org/C2780695682","wikidata":"https://www.wikidata.org/wiki/Q4005959","display_name":"Jump","level":2,"score":0.6476502418518066},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6177261471748352},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.5283390283584595},{"id":"https://openalex.org/C2986379492","wikidata":"https://www.wikidata.org/wiki/Q1638492","display_name":"Continuous glucose monitoring","level":4,"score":0.46212005615234375},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.42537280917167664},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4167099595069885},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41232264041900635},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3672561049461365},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.35943639278411865},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2655814588069916},{"id":"https://openalex.org/C2781232474","wikidata":"https://www.wikidata.org/wiki/Q124407","display_name":"Type 1 diabetes","level":3,"score":0.20088785886764526},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.19804871082305908},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1353083848953247},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1261291801929474},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.08756858110427856},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccicc46617.2019.9146049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccicc46617.2019.9146049","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 18th International Conference on Cognitive Informatics &amp; Cognitive Computing (ICCI*CC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.6700000166893005,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1986815545","https://openalex.org/W2003643515","https://openalex.org/W2008275110","https://openalex.org/W2008348094","https://openalex.org/W2019652008","https://openalex.org/W2031602193","https://openalex.org/W2087494823","https://openalex.org/W2101539208","https://openalex.org/W2104152234","https://openalex.org/W2107093743","https://openalex.org/W2123360522","https://openalex.org/W2123946565","https://openalex.org/W2141514928","https://openalex.org/W2164274563","https://openalex.org/W2427205197","https://openalex.org/W2521641300","https://openalex.org/W2565516711","https://openalex.org/W2592929672","https://openalex.org/W2620050178","https://openalex.org/W2753484035","https://openalex.org/W2793729473","https://openalex.org/W2803696067","https://openalex.org/W2888806317","https://openalex.org/W2889087356","https://openalex.org/W2889292359","https://openalex.org/W2903071242","https://openalex.org/W2913265378","https://openalex.org/W2963218601","https://openalex.org/W4243273793","https://openalex.org/W6753907178","https://openalex.org/W6754420901","https://openalex.org/W6756472356"],"related_works":["https://openalex.org/W4380075502","https://openalex.org/W4223943233","https://openalex.org/W4312200629","https://openalex.org/W4360585206","https://openalex.org/W4364306694","https://openalex.org/W4380086463","https://openalex.org/W4225161397","https://openalex.org/W3014300295","https://openalex.org/W3164822677","https://openalex.org/W4250304930"],"abstract_inverted_index":{"Type":[0],"1":[1],"diabetes":[2],"mellitus":[3],"is":[4,84,182],"a":[5,95,115],"widespread":[6],"chronic":[7],"disease":[8],"that,":[9],"if":[10],"not":[11],"properly":[12],"treated,":[13],"can":[14],"lead":[15],"to":[16,36,73,132,142,163],"short-":[17],"and":[18,47,99,136,156],"longterm":[19],"complications.":[20],"In":[21],"recent":[22],"years,":[23],"continuous":[24],"glucose":[25,40,62],"monitoring":[26],"has":[27],"become":[28],"very":[29],"popular":[30],"among":[31],"patients":[32],"since":[33],"it":[34],"allows":[35],"keep":[37],"track":[38],"of":[39,57,80],"levels":[41,63],"for":[42],"24":[43],"hours.":[44],"Nevertheless,":[45],"hypo-":[46],"hyperglycemic":[48],"events":[49],"are":[50,161],"still":[51],"widely":[52],"reported,":[53],"motivating":[54],"the":[55,81,89,104,121,130,133,140,143,168,172,175],"development":[56],"methods":[58],"that":[59,91,119],"forecast":[60],"blood":[61],"at":[64,153],"given":[65],"prediction":[66,158],"horizons,":[67,159],"which":[68,160],"usually":[69,93],"range":[70],"from":[71,103,129,139],"15":[72],"30":[74],"minutes.":[75],"However":[76],"their":[77],"application,":[78],"regardless":[79],"approaches":[82],"adopted,":[83],"limited":[85],"in":[86,110,171,179],"practice":[87],"by":[88,125],"fact":[90],"they":[92],"need":[94],"long":[96],"training":[97,176],"time":[98,127],"other":[100],"information":[101],"gathered":[102],"patients.":[105],"To":[106],"overcome":[107],"these":[108],"issues":[109],"this":[111,180],"work":[112,181],"we":[113],"present":[114],"new":[116],"neural":[117,148],"network":[118,123,149],"extends":[120],"jump":[122],"model":[124],"introducing":[126],"delays":[128],"input":[131],"hidden":[134,144],"layer":[135],"auto-regressive":[137],"feedback":[138],"output":[141],"layer.":[145],"The":[146],"proposed":[147],"shows":[150],"promising":[151],"results":[152,169],"15,":[154],"20":[155],"30-minute":[157],"comparable":[162],"or":[164],"slightly":[165],"better":[166],"than":[167],"reported":[170],"literature,":[173],"although":[174],"period":[177],"used":[178],"considerably":[183],"shorter.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
