{"id":"https://openalex.org/W4415399144","doi":"https://doi.org/10.1109/spml66318.2025.11199762","title":"Hypertension Risk Prediction Model Based on Multilabel Classification","display_name":"Hypertension Risk Prediction Model Based on Multilabel Classification","publication_year":2025,"publication_date":"2025-07-15","ids":{"openalex":"https://openalex.org/W4415399144","doi":"https://doi.org/10.1109/spml66318.2025.11199762"},"language":"en","primary_location":{"id":"doi:10.1109/spml66318.2025.11199762","doi":"https://doi.org/10.1109/spml66318.2025.11199762","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spml66318.2025.11199762","pdf_url":null,"source":{"id":"https://openalex.org/S7407106287","display_name":"IEEE International Conference on Signal Processing and Machine Learning (SPML)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 8th International Conference on Signal Processing and Machine Learning (SPML)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5120084095","display_name":"Lu Yajing","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Yajing","raw_affiliation_strings":["School of electronic information Xijing University,Xi'an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of electronic information Xijing University,Xi'an,China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120084096","display_name":"Nie Xiaorui","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nie Xiaorui","raw_affiliation_strings":["School of electronic information Xijing University,Xi'an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of electronic information Xijing University,Xi'an,China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120084097","display_name":"Xu Guirue","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Guirue","raw_affiliation_strings":["School of electronic information Xijing University,Xi'an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of electronic information Xijing University,Xi'an,China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120084098","display_name":"Li Baochu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Baochu","raw_affiliation_strings":["School of electronic information Xijing University,Xi'an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of electronic information Xijing University,Xi'an,China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108995580","display_name":"Yuhong Xing","orcid":"https://orcid.org/0009-0001-6286-8732","observed_orcids":["https://orcid.org/0009-0001-6286-8732"]},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Yuhong","raw_affiliation_strings":["School of electronic information Xijing University,Xi'an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of electronic information Xijing University,Xi'an,China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120084100","display_name":"Deng Qinli","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Deng Qinli","raw_affiliation_strings":["School of electronic information Xijing University,Xi'an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of electronic information Xijing University,Xi'an,China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101500889","display_name":"Yahong Ma","orcid":"https://orcid.org/0000-0002-4294-0186","observed_orcids":["https://orcid.org/0000-0002-4294-0186"]},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ma Yahong","raw_affiliation_strings":["School of electronic information Xijing University,Xi'an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of electronic information Xijing University,Xi'an,China","institution_ids":["https://openalex.org/I4210162994"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210162994"],"apc_list":null,"apc_paid":null,"fwci":1.1601,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.67679064,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"544","last_page":"548"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9779999852180481,"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"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9779999852180481,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.011800000444054604,"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/T10144","display_name":"Blood Pressure and Hypertension Studies","score":0.003599999938160181,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/hypertension-prediction","display_name":"hypertension risk prediction","score":0.984000027179718},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"multi-label classification","score":0.9160000085830688},{"id":"https://openalex.org/keywords/knowledge-graph-embedding","display_name":"knowledge graph embedding","score":0.9789999723434448},{"id":"https://openalex.org/keywords/bidirectional-lstm","display_name":"bidirectional LSTM","score":0.8870000243186951},{"id":"https://openalex.org/keywords/self-attention","display_name":"self-attention","score":0.7630000114440918},{"id":"https://openalex.org/keywords/cardiovascular-disease","display_name":"cardiovascular disease","score":0.5299999713897705}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6711000204086304},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6065999865531921},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5787000060081482},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5149000287055969},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5073000192642212},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4108999967575073},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.39739999175071716},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.35989999771118164},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35100001096725464},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.33709999918937683},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.3156000077724457},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.3075000047683716},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25870001316070557}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/spml66318.2025.11199762","doi":"https://doi.org/10.1109/spml66318.2025.11199762","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spml66318.2025.11199762","pdf_url":null,"source":{"id":"https://openalex.org/S7407106287","display_name":"IEEE International Conference on Signal Processing and Machine Learning (SPML)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 8th International Conference on Signal Processing and Machine Learning (SPML)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.9763000011444092}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2050661717","https://openalex.org/W2899773405","https://openalex.org/W2953282350","https://openalex.org/W4319035125","https://openalex.org/W4381951082","https://openalex.org/W4391424767","https://openalex.org/W4393054355","https://openalex.org/W4393932307","https://openalex.org/W4394952741","https://openalex.org/W4399040281","https://openalex.org/W4401179044","https://openalex.org/W4409906357"],"related_works":["https://openalex.org/W4414833409","https://openalex.org/W7171398044","https://openalex.org/W3161194468","https://openalex.org/W7160924052","https://openalex.org/W7160321518","https://openalex.org/W7133502415","https://openalex.org/W7165134632","https://openalex.org/W7117753991","https://openalex.org/W4416677377","https://openalex.org/W7082380021"],"abstract_inverted_index":{"Hypertension,":[0],"as":[1,104],"a":[2,20],"common":[3],"chronic":[4],"disease,":[5],"its":[6],"early":[7],"prediction":[8,124],"and":[9,44,61,80,125],"intervention":[10],"are":[11],"crucial":[12],"for":[13,121],"reducing":[14],"cardiovascular":[15],"events.":[16],"This":[17],"paper":[18],"proposes":[19],"multi-label":[21],"classification":[22,74],"model":[23,71,86,116],"called":[24],"-":[25],"KGAC-Bi-LSTM,":[26],"which":[27],"is":[28],"based":[29],"on":[30],"knowledge":[31],"graph":[32],"embedding,":[33],"convolutional":[34],"neural":[35],"network":[36,42],"(CNN),":[37],"bidirectional":[38],"long":[39],"short-term":[40],"memory":[41],"(BiLSTM),":[43],"attention":[45],"mechanisms,":[46],"to":[47],"accurately":[48],"predict":[49],"hypertension":[50,55,96,122],"risk.":[51],"By":[52],"processing":[53],"the":[54,58,63,69,84,93,115],"dataset":[56],"from":[57],"Kaggle":[59],"platform":[60],"training":[62],"model,":[64],"experimental":[65],"results":[66],"show":[67],"that":[68,114],"KGAC-Bi-LSTM":[70],"outperforms":[72],"traditional":[73],"methods":[75],"in":[76],"accuracy,":[77],"generalization":[78],"ability,":[79],"stability.":[81],"In":[82],"addition,":[83],"KGASA-Bi-LSTM":[85],"combined":[87],"with":[88,100],"self-attention":[89],"mechanism":[90],"further":[91],"improves":[92],"accuracy":[94,102],"of":[95],"risk":[97,123],"category":[98],"identification,":[99],"an":[101,118],"rate":[103],"high":[105],"as$\\mathbf{9":[106],"6.":[107],"3":[108],"7":[109],"\\%}$.":[110],"The":[111],"experiment":[112],"shows":[113],"provides":[117],"effective":[119],"solution":[120],"has":[126],"great":[127],"practical":[128],"application":[129],"value.":[130]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2025-10-22T00:00:00"}
