{"id":"https://openalex.org/W66168305","doi":null,"title":"Wrapper subset evaluation facilitates the automated detection of diabetes from heart rate variability measures","display_name":"Wrapper subset evaluation facilitates the automated detection of diabetes from heart rate variability measures","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W66168305","mag":"66168305"},"language":"en","primary_location":{"id":"pmh:oai:pure.atira.dk:publications/729e217c-3ac3-4918-8975-29b8451596b1","doi":null,"is_oa":true,"landing_page_url":"https://researchoutput.csu.edu.au/en/publications/729e217c-3ac3-4918-8975-29b8451596b1","pdf_url":null,"source":{"id":"https://openalex.org/S7407055442","display_name":"Charles Sturt University Research Output (CRO)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Cornforth, D, Jelinek, H, Teich, M & Lowen, S 2004, Wrapper subset evaluation facilitates the automated detection of diabetes from heart rate variability measures. in M Mohammadian (ed.), CIMCA 2004 : International Conference on Computational Intelligence for Modelling, Control & Automation. University of Canberra, Canberra, Australia, pp. 446-455, International Conference on Computational Intelligence for Modelling, Control and Automation, Australia, 12/07/04.","raw_type":"info:eu-repo/semantics/conferenceObject"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://researchoutput.csu.edu.au/en/publications/729e217c-3ac3-4918-8975-29b8451596b1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072557235","display_name":"David J. Cornforth","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David Cornforth","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011347476","display_name":"Herbert Franz Jelinek","orcid":"https://orcid.org/0000-0001-5457-6193","observed_orcids":["https://orcid.org/0000-0001-5457-6193"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Herbert F. Jelinek","raw_affiliation_strings":["Community Health"],"raw_orcid":"https://orcid.org/0000-0001-5457-6193","affiliations":[{"raw_affiliation_string":"Community Health","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058287918","display_name":"Malvin Carl Teich","orcid":"https://orcid.org/0000-0001-8164-4622","observed_orcids":["https://orcid.org/0000-0001-8164-4622"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marvin Teich","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5047078330","display_name":"Steven Bradley Lowen","orcid":"https://orcid.org/0000-0002-5243-2548","observed_orcids":["https://orcid.org/0000-0002-5243-2548"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Steve Lowen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.00791557,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"446","last_page":"455"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9380000233650208,"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"}},"topics":[{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9380000233650208,"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"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.04780000075697899,"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.0017999999690800905,"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/diabetes-detection","display_name":"diabetes detection","score":0.9390000104904175},{"id":"https://openalex.org/keywords/heart-rate-variability","display_name":"heart rate variability","score":0.9990000128746033},{"id":"https://openalex.org/keywords/cardiac-autonomic-neuropathy","display_name":"cardiac autonomic neuropathy","score":0.9319999814033508},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.8270000219345093},{"id":"https://openalex.org/keywords/automated-machine-learning","display_name":"automated machine learning","score":0.921999990940094},{"id":"https://openalex.org/keywords/classifier-comparison","display_name":"classifier comparison","score":0.593999981880188},{"id":"https://openalex.org/keywords/sensitivity-and-specificity","display_name":"sensitivity and specificity","score":0.7889999747276306},{"id":"https://openalex.org/keywords/early-diagnosis-of-diabetes","display_name":"early detection of diabetes","score":0.6449999809265137},{"id":"https://openalex.org/keywords/wavelet-analysis","display_name":"wavelet analysis","score":0.6610000133514404},{"id":"https://openalex.org/keywords/fractal-analysis","display_name":"fractal analysis","score":0.9610000252723694},{"id":"https://openalex.org/keywords/cardiac-arrhythmia","display_name":"cardiac arrhythmias","score":0.5479999780654907},{"id":"https://openalex.org/keywords/heart-failure","display_name":"heart failure","score":0.6150000095367432},{"id":"https://openalex.org/keywords/stroke-risk","display_name":"stroke risk","score":0.8629999756813049},{"id":"https://openalex.org/keywords/healthcare-cost-reduction","display_name":"healthcare cost reduction","score":0.5230000019073486}],"concepts":[{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.710088312625885},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.6996433734893799},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5645620226860046},{"id":"https://openalex.org/C2778198053","wikidata":"https://www.wikidata.org/wiki/Q181754","display_name":"Heart failure","level":2,"score":0.48545700311660767},{"id":"https://openalex.org/C2780645631","wikidata":"https://www.wikidata.org/wiki/Q671554","display_name":"Stroke (engine)","level":2,"score":0.47905147075653076},{"id":"https://openalex.org/C179755657","wikidata":"https://www.wikidata.org/wiki/Q58702","display_name":"Mortality rate","level":2,"score":0.4661693871021271},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.447157084941864},{"id":"https://openalex.org/C2780074459","wikidata":"https://www.wikidata.org/wiki/Q389735","display_name":"Heart disease","level":2,"score":0.4236457049846649},{"id":"https://openalex.org/C177713679","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care medicine","level":1,"score":0.3733323812484741},{"id":"https://openalex.org/C194828623","wikidata":"https://www.wikidata.org/wiki/Q2861470","display_name":"Emergency medicine","level":1,"score":0.3359360694885254},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.2478092908859253},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.19561192393302917},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08237439393997192},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","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},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:pure.atira.dk:publications/729e217c-3ac3-4918-8975-29b8451596b1","doi":null,"is_oa":true,"landing_page_url":"https://researchoutput.csu.edu.au/en/publications/729e217c-3ac3-4918-8975-29b8451596b1","pdf_url":null,"source":{"id":"https://openalex.org/S7407055442","display_name":"Charles Sturt University Research Output (CRO)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Cornforth, D, Jelinek, H, Teich, M & Lowen, S 2004, Wrapper subset evaluation facilitates the automated detection of diabetes from heart rate variability measures. in M Mohammadian (ed.), CIMCA 2004 : International Conference on Computational Intelligence for Modelling, Control & Automation. University of Canberra, Canberra, Australia, pp. 446-455, International Conference on Computational Intelligence for Modelling, Control and Automation, Australia, 12/07/04.","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"mag:66168305","doi":null,"is_oa":false,"landing_page_url":"http://people.bu.edu/teich/pdfs/PROC-CIMCA-446-2004.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306417935","display_name":"Computational Intelligence for Modelling, Control and Automation","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Computational Intelligence for Modelling, Control and Automation","raw_type":null}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:publications/729e217c-3ac3-4918-8975-29b8451596b1","doi":null,"is_oa":true,"landing_page_url":"https://researchoutput.csu.edu.au/en/publications/729e217c-3ac3-4918-8975-29b8451596b1","pdf_url":null,"source":{"id":"https://openalex.org/S7407055442","display_name":"Charles Sturt University Research Output (CRO)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Cornforth, D, Jelinek, H, Teich, M & Lowen, S 2004, Wrapper subset evaluation facilitates the automated detection of diabetes from heart rate variability measures. in M Mohammadian (ed.), CIMCA 2004 : International Conference on Computational Intelligence for Modelling, Control & Automation. University of Canberra, Canberra, Australia, pp. 446-455, International Conference on Computational Intelligence for Modelling, Control and Automation, Australia, 12/07/04.","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[{"score":1.0,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W57178471","https://openalex.org/W166770137","https://openalex.org/W186911049","https://openalex.org/W1497256448","https://openalex.org/W1630964756","https://openalex.org/W1676820704","https://openalex.org/W1928670660","https://openalex.org/W1972728773","https://openalex.org/W1984561364","https://openalex.org/W1993740947","https://openalex.org/W2001619934","https://openalex.org/W2004968413","https://openalex.org/W2017337590","https://openalex.org/W2040615655","https://openalex.org/W2123504579","https://openalex.org/W2129905273","https://openalex.org/W2149706766","https://openalex.org/W2154551745","https://openalex.org/W2159012223","https://openalex.org/W2285072859","https://openalex.org/W2473732573","https://openalex.org/W2966207845","https://openalex.org/W3017143921","https://openalex.org/W3083113686","https://openalex.org/W3121299688","https://openalex.org/W3139831614"],"related_works":["https://openalex.org/W2116570678","https://openalex.org/W2025056501","https://openalex.org/W2009787667","https://openalex.org/W2001905743","https://openalex.org/W3193468129","https://openalex.org/W2761972966","https://openalex.org/W2291156680","https://openalex.org/W7029197380","https://openalex.org/W2313824304","https://openalex.org/W2403295091"],"abstract_inverted_index":{"Abstract":[0],"Diabetes":[1,281],"affects":[2,262],"almost":[3],"one":[4],"million":[5,175],"Australians,":[6],"and":[7,20,39,52,109,140,150,181,201,208,224,268,299,318,322,335,341,397,451],"is":[8,124,402,426,437,468],"associated":[9,185,244],"with":[10,33,156,186,278,307,333],"many":[11,387],"other":[12],"conditions":[13],"such":[14,219,255],"as":[15,98,220,228,256,343,345,405,421],"vision":[16],"loss,":[17,198],"heart":[18,58,127,199,222,267,288,339,378],"failure":[19,200,301,340],"stroke.":[21],"Any":[22],"improvement":[23],"in":[24,160,234,238,272,287,297,302,362,375],"early":[25],"diagnosis":[26,69],"would":[27,314,325],"therefore":[28],"represent":[29,449,462],"a":[30,101,148,348,406,427,443,452,458],"significant":[31,149],"gain":[32],"respect":[34],"to":[35,56,67,80,90,96,100,146,162,166,191,205,274,284,347,351,438],"reducing":[36],"the":[37,42,68,77,92,120,135,157,206,211,216,229,263,266,303,327,352,360,363,367,435],"morbidity":[38,207,321],"mortality":[40,209],"of":[41,70,103,122,138,188,210,215,232,236,251,265,276,305,311,329,366,377,385,395,415,430,445,455],"Australian":[43,212],"population.":[44,213],"In":[45,171,247],"this":[46,312,383],"study":[47],"we":[48,75,87],"apply":[49],"signal":[50],"processing":[51],"automated":[53],"machine":[54,431],"learning":[55,432],"analyse":[57],"rate":[59,128,289,379],"variability":[60,129,290,380],"measures.":[61],"These":[62],"data":[63],"are":[64,177],"well":[65,344,403],"suited":[66],"cardiac":[71,257,300,410],"dysfunction,":[72],"but":[73],"here":[74],"use":[76,97,394],"same":[78],"measures":[79,130,389],"detect":[81],"diabetes.":[82,308],"By":[83],"applying":[84,471],"appropriate":[85],"methods":[86],"were":[88,226],"able":[89],"select":[91],"most":[93],"relevant":[94],"features":[95],"input":[99,446],"variety":[102],"classifier":[104,115],"algorithms.":[105,116],"We":[106],"compare":[107],"sensitivity":[108],"specificity":[110],"results":[111],"obtained":[112,469],"from":[113,126,164],"these":[114],"Results":[117],"suggest":[118],"that":[119,261,291,448,461],"detection":[121,310],"diabetes":[123,145,180,241,279,334],"feasible":[125],".":[131],"1.":[132],"Introduction":[133],"Both":[134],"NSW":[136],"Department":[137],"Health":[139],"Commonwealth":[141],"Government":[142],"have":[143],"identified":[144],"be":[147,373,391],"growing":[151],"global":[152],"public":[153],"health":[154,182,353],"problem":[155],"expected":[158],"incidence":[159],"Australia":[161,172,485],"increase":[163],"4%":[165],"10%":[167],"by":[168,179,470],"2010":[169],"[1].":[170],"approximately":[173,192],"1":[174],"people":[176,277,332],"affected":[178],"care":[183,354],"costs":[184],"treatment":[187],"complications":[189],"amounts":[190],"$7":[193],"billion":[194],"dollars":[195],"[2].":[196],"Vision":[197],"stroke":[202,225],"contribute":[203],"significantly":[204],"Diseases":[214],"circulatory":[217],"system":[218,253,355],"coronary":[221],"disease":[223],"listed":[227],"underlying":[230],"cause":[231,245],"death":[233],"55.7%":[235],"deaths":[237],"2000":[239],"where":[240],"was":[242],"an":[243,472],"[3].":[246],"addition":[248],"some":[249,440],"form":[250],"nervous":[252],"damage":[254],"autonomic":[258],"neuropathy":[259],"(CAN)":[260],"function":[264],"blood":[269],"vessels,":[270],"occurs":[271],"up":[273],"60-70%":[275],"[4].":[280],"may":[282,390],"lead":[283],"subtle":[285],"changes":[286],"become":[292],"increasingly":[293],"more":[294],"compromising,":[295],"manifesting":[296],"arrhythmia":[298],"majority":[304],"individuals":[306],"Early":[309],"pathology":[313],"allow":[315],"timely":[316],"intervention":[317],"thus":[319],"lessen":[320],"mortality.":[323],"This":[324],"improve":[326],"quality":[328],"life":[330],"for":[331,338,408],"at":[336],"risk":[337],"stroke,":[342],"contributing":[346],"substantial":[349],"saving":[350],"[5].":[356],"To":[357],"assess":[358],"CAN":[359],"variation":[361],"interval":[364],"length":[365],"ECG":[368],"between":[369,442],"successive":[370],"beats":[371],"can":[372],"analyzed":[374],"terms":[376],"(HRV).":[381],"From":[382],"sequence":[384],"intervals,":[386],"secondary":[388],"derived,":[392],"making":[393],"fractal":[396],"wavelet":[398],"analysis":[399],"techniques.":[400],"It":[401],"known":[404],"tool":[407],"detecting":[409],"dysfunction":[411],"[6,":[412],"7].":[413],"Discrimination":[414],"various":[416],"categories":[417],"or":[418,424,464],"classes":[419],"(such":[420],"\u201ccardiac":[422],"dysfunction\u201d":[423],"\u201cnormal\u201d)":[425],"well-studied":[428],"class":[429],"problems.":[433],"Here":[434],"key":[436],"determine":[439],"relationship":[441,467],"set":[444,454],"vectors":[447],"stimuli,":[450],"corresponding":[453],"values":[456],"on":[457],"nominal":[459],"scale":[460],"category":[463],"class.":[465],"The":[466],"CIMCA":[473],"2004":[474],"Proceedings/ISBN":[475],":1740881885":[476],"M.":[477],"Mohammadian":[478],"(Ed.)12-14":[479],"July":[480],"2004,":[481],"Gold":[482],"Coast":[483],"-":[484]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-10-12T09:40:04.860316","created_date":"2016-06-24T00:00:00"}
