{"id":"https://openalex.org/W2407043862","doi":"https://doi.org/10.1109/mlsp.2016.7738901","title":"Automatic classification of irregularly sampled time series with unequal lengths: A case study on estimated glomerular filtration rate","display_name":"Automatic classification of irregularly sampled time series with unequal lengths: A case study on estimated glomerular filtration rate","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2407043862","doi":"https://doi.org/10.1109/mlsp.2016.7738901","mag":"2407043862"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2016.7738901","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2016.7738901","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1605.05142","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013246415","display_name":"Santosh Tirunagari","orcid":"https://orcid.org/0000-0002-9064-1965"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Santosh Tirunagari","raw_affiliation_strings":["Department of Computer Science, University of Surrey, Guildford, Surrey","Department of Computer Science, University of Surrey, Guildford, Surrey GU2 7XH"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Surrey, Guildford, Surrey","institution_ids":["https://openalex.org/I28290843"]},{"raw_affiliation_string":"Department of Computer Science, University of Surrey, Guildford, Surrey GU2 7XH","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008324143","display_name":"Simon Bull","orcid":null},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Simon Bull","raw_affiliation_strings":["Department of Computer Science, University of Surrey, Guildford, Surrey","Department of Computer Science, University of Surrey, Guildford, Surrey GU2 7XH"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Surrey, Guildford, Surrey","institution_ids":["https://openalex.org/I28290843"]},{"raw_affiliation_string":"Department of Computer Science, University of Surrey, Guildford, Surrey GU2 7XH","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029657515","display_name":"Norman Poh","orcid":"https://orcid.org/0000-0001-6076-0309"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Norman Poh","raw_affiliation_strings":["Department of Computer Science, University of Surrey, Guildford, Surrey","Department of Computer Science, University of Surrey, Guildford, Surrey GU2 7XH"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Surrey, Guildford, Surrey","institution_ids":["https://openalex.org/I28290843"]},{"raw_affiliation_string":"Department of Computer Science, University of Surrey, Guildford, Surrey GU2 7XH","institution_ids":["https://openalex.org/I28290843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I28290843"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02801054,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9991000294685364,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/resampling","display_name":"Resampling","score":0.6465151309967041},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.63709956407547},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5991040468215942},{"id":"https://openalex.org/keywords/renal-function","display_name":"Renal function","score":0.5468471050262451},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5287261605262756},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5099631547927856},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4710257947444916},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.4670962691307068},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44248664379119873},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4401066303253174},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4175722897052765},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4040694534778595},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.36885297298431396},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35382145643234253},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3471553325653076},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3457219898700714},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.19774731993675232},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.13477545976638794},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.11481234431266785}],"concepts":[{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.6465151309967041},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.63709956407547},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5991040468215942},{"id":"https://openalex.org/C159641895","wikidata":"https://www.wikidata.org/wiki/Q108377937","display_name":"Renal function","level":2,"score":0.5468471050262451},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5287261605262756},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5099631547927856},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4710257947444916},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.4670962691307068},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44248664379119873},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4401066303253174},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4175722897052765},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4040694534778595},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.36885297298431396},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35382145643234253},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3471553325653076},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3457219898700714},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.19774731993675232},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.13477545976638794},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.11481234431266785},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/mlsp.2016.7738901","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2016.7738901","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1605.05142","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1605.05142","pdf_url":"https://arxiv.org/pdf/1605.05142","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:epubs.surrey.ac.uk:812518","is_oa":false,"landing_page_url":"http://epubs.surrey.ac.uk/812518/1/AKI_paper.pdf","pdf_url":"http://epubs.surrey.ac.uk/812518/1/AKI_paper.pdf","source":{"id":"https://openalex.org/S4306400680","display_name":"Surrey Research Insight Open Access (The University of Surrey)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28290843","host_organization_name":"University of Surrey","host_organization_lineage":["https://openalex.org/I28290843"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"},{"id":"mag:2407043862","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1605.05142.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1605.05142","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1605.05142","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1605.05142","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1605.05142","pdf_url":"https://arxiv.org/pdf/1605.05142","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.47999998927116394}],"awards":[{"id":"https://openalex.org/G2167796806","display_name":null,"funder_award_id":"MR/M023281/1","funder_id":"https://openalex.org/F4320334626","funder_display_name":"Medical Research Council"}],"funders":[{"id":"https://openalex.org/F4320334626","display_name":"Medical Research Council","ror":"https://ror.org/03x94j517"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2407043862.pdf","grobid_xml":"https://content.openalex.org/works/W2407043862.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W316307590","https://openalex.org/W1502922572","https://openalex.org/W1746819321","https://openalex.org/W1977512462","https://openalex.org/W1986195997","https://openalex.org/W2086972503","https://openalex.org/W2107386393","https://openalex.org/W2118843652","https://openalex.org/W2120236826","https://openalex.org/W2400373170","https://openalex.org/W2542969993","https://openalex.org/W6605568159"],"related_works":["https://openalex.org/W2963674026","https://openalex.org/W2339801123","https://openalex.org/W3203359490","https://openalex.org/W2747672283","https://openalex.org/W2097158593","https://openalex.org/W2539016236","https://openalex.org/W3121033296","https://openalex.org/W2557901506","https://openalex.org/W2086678077","https://openalex.org/W3089326207","https://openalex.org/W2594785165"],"abstract_inverted_index":{"A":[0],"patient's":[1],"estimated":[2],"glomerular":[3],"filtration":[4],"rate":[5],"(eGFR)":[6],"can":[7],"provide":[8],"important":[9],"information":[10],"about":[11],"disease":[12],"progression":[13],"and":[14,74,133],"kidney":[15],"function.":[16],"Traditionally,":[17],"an":[18,93,146],"eGFR":[19,66,94,126],"time":[20,42,100,127],"series":[21,76,101,128],"is":[22],"interpreted":[23],"by":[24,111],"a":[25,87,113,130],"human":[26,155],"expert":[27],"labelling":[28],"it":[29,46],"as":[30,65],"stable":[31],"or":[32],"unstable.":[33],"While":[34],"this":[35,60,142],"approach":[36,143],"works":[37],"for":[38,153],"individual":[39],"patients,":[40],"the":[41,48,75,99,124],"consuming":[43],"nature":[44],"of":[45,51,56,77,117,148],"precludes":[47],"quick":[49],"evaluation":[50],"risk":[52],"in":[53,80,109],"large":[54],"numbers":[55],"patients.":[57,83],"However,":[58],"automating":[59],"process":[61,104],"poses":[62],"significant":[63],"challenges":[64],"measurements":[67,78],"are":[68],"usually":[69],"recorded":[70],"at":[71],"irregular":[72],"intervals":[73],"differs":[79],"length":[81],"between":[82],"Here":[84],"we":[85,97,122,144],"present":[86],"two-tier":[88],"system":[89],"to":[90,107,151],"automatically":[91],"classify":[92,123],"trend.":[95],"First,":[96],"model":[98],"using":[102,129],"Gaussian":[103],"regression":[105],"(GPR)":[106],"fill":[108],"`gaps'":[110],"resampling":[112],"fixed":[114],"size":[115],"vector":[116],"fifty":[118],"time-dependent":[119],"observations.":[120],"Second,":[121],"resampled":[125],"K-NN/SVM":[131],"classifier,":[132],"evaluate":[134],"its":[135],"performance":[136],"via":[137],"5-fold":[138],"cross":[139],"validation.":[140],"Using":[141],"achieved":[145],"F-score":[147],"0.90,":[149],"compared":[150],"0.96":[152],"5":[154],"experts":[156],"when":[157],"scored":[158],"amongst":[159],"themselves.":[160]},"counts_by_year":[],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}