{"id":"https://openalex.org/W4392910330","doi":"https://doi.org/10.1109/icassp48485.2024.10446832","title":"Predicting Adverse Events for Patients with Type-1 Diabetes Via Self-Supervised Learning","display_name":"Predicting Adverse Events for Patients with Type-1 Diabetes Via Self-Supervised Learning","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392910330","doi":"https://doi.org/10.1109/icassp48485.2024.10446832"},"language":"en","primary_location":{"id":"doi:10.1109/icassp48485.2024.10446832","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10446832","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"article","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/A5077510260","display_name":"Xinzhe Zheng","orcid":"https://orcid.org/0000-0002-6215-0069"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Xinzhe Zheng","raw_affiliation_strings":["The University of Hong Kong,Department of Computer Science","Department of Computer Science, The University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Department of Computer Science","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"Department of Computer Science, The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059429176","display_name":"Sijie Ji","orcid":"https://orcid.org/0000-0002-6615-1982"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Sijie Ji","raw_affiliation_strings":["The University of Hong Kong,Department of Computer Science","Department of Computer Science, The University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Department of Computer Science","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"Department of Computer Science, The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080848262","display_name":"Chenshu Wu","orcid":"https://orcid.org/0000-0002-9700-4627"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Chenshu Wu","raw_affiliation_strings":["The University of Hong Kong,Department of Computer Science","Department of Computer Science, The University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Department of Computer Science","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"Department of Computer Science, The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077510260"],"corresponding_institution_ids":["https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":2.3857,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.89372588,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1526","last_page":"1530"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10560","display_name":"Diabetes Management and Research","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9937000274658203,"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"}},{"id":"https://openalex.org/T11623","display_name":"Hyperglycemia and glycemic control in critically ill and hospitalized patients","score":0.9671000242233276,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6963474750518799},{"id":"https://openalex.org/keywords/hypoglycemia","display_name":"Hypoglycemia","score":0.6880598068237305},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6465471982955933},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6403095126152039},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5992937088012695},{"id":"https://openalex.org/keywords/adverse-effect","display_name":"Adverse effect","score":0.5110188722610474},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49165087938308716},{"id":"https://openalex.org/keywords/type-2-diabetes","display_name":"Type 2 diabetes","score":0.46407416462898254},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4335176944732666},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"Diabetes mellitus","score":0.36295926570892334},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.271664559841156},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.22721236944198608},{"id":"https://openalex.org/keywords/endocrinology","display_name":"Endocrinology","score":0.08675166964530945}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6963474750518799},{"id":"https://openalex.org/C2780668416","wikidata":"https://www.wikidata.org/wiki/Q202758","display_name":"Hypoglycemia","level":3,"score":0.6880598068237305},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6465471982955933},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6403095126152039},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5992937088012695},{"id":"https://openalex.org/C197934379","wikidata":"https://www.wikidata.org/wiki/Q2047938","display_name":"Adverse effect","level":2,"score":0.5110188722610474},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49165087938308716},{"id":"https://openalex.org/C2777180221","wikidata":"https://www.wikidata.org/wiki/Q3025883","display_name":"Type 2 diabetes","level":3,"score":0.46407416462898254},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4335176944732666},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.36295926570892334},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.271664559841156},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.22721236944198608},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.08675166964530945},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp48485.2024.10446832","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10446832","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8676120579","display_name":null,"funder_award_id":"62222216","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2004870840","https://openalex.org/W2009177416","https://openalex.org/W2013665941","https://openalex.org/W2038343656","https://openalex.org/W2148143831","https://openalex.org/W2470196169","https://openalex.org/W2736029153","https://openalex.org/W2896457183","https://openalex.org/W2897666265","https://openalex.org/W2910797899","https://openalex.org/W2963351448","https://openalex.org/W2964110616","https://openalex.org/W3008906415","https://openalex.org/W3091277071","https://openalex.org/W3189373506","https://openalex.org/W3211771663","https://openalex.org/W4205203504","https://openalex.org/W4225325459","https://openalex.org/W4313156423","https://openalex.org/W4313525398","https://openalex.org/W4386096129","https://openalex.org/W6755207826","https://openalex.org/W6783880471","https://openalex.org/W6784018277"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W3088732000"],"abstract_inverted_index":{"Predicting":[0],"blood":[1,52,68],"glucose":[2,21,53,69,114],"levels":[3,22],"is":[4,17],"fundamental":[5],"for":[6,51,71],"precise":[7],"primary":[8],"care":[9],"of":[10,30,67,130],"type-1":[11],"diabetes":[12],"(T1D)":[13],"patients.":[14],"However,":[15],"it":[16],"challenging":[18],"to":[19,25,62,84,123],"predict":[20],"accurately,":[23],"not":[24],"mention":[26],"the":[27,37,107],"early":[28],"alarm":[29],"adverse":[31,87,124],"events":[32,88],"(hyperglycemia":[33],"and":[34,79,121,132],"hypoglycemia),":[35],"namely":[36],"minority":[38],"class.":[39],"In":[40,56],"this":[41],"paper,":[42],"we":[43],"propose":[44],"BG-BERT,":[45],"a":[46],"novel":[47],"self-supervised":[48],"learning":[49],"framework":[50],"level":[54,115],"prediction.":[55,73],"particular,":[57],"BG-BERT":[58,93,112],"incorporates":[59],"masked":[60],"autoencoder":[61],"capture":[63],"rich":[64],"contextual":[65],"information":[66],"records":[70],"accurate":[72],"More":[74],"specifically,":[75],"SMOTE":[76],"data":[77],"augmentation":[78],"shrinkage":[80],"loss":[81],"are":[82],"employed":[83],"effectively":[85],"handle":[86],"without":[89],"discrimination.":[90],"We":[91],"evaluate":[92],"on":[94],"two":[95,99],"benchmark":[96],"datasets":[97],"against":[98],"state-of-the-art":[100],"base-line":[101],"models.":[102],"The":[103],"experimental":[104],"results":[105],"highlight":[106],"significant":[108],"improvements":[109],"achieved":[110],"by":[111,119],"in":[113],"prediction":[116],"accuracy":[117],"(measured":[118],"RMSE)":[120],"sensitivity":[122],"events,":[125],"with":[126],"average":[127],"lifting":[128],"ratios":[129],"9.5%":[131],"44.9%,":[133],"respectively.":[134]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-23T09:07:50.710637","created_date":"2025-10-10T00:00:00"}