{"id":"https://openalex.org/W2888870618","doi":"https://doi.org/10.3390/s18092857","title":"Towards an Efficient One-Class Classifier for Mobile Devices and Wearable Sensors on the Context of Personal Risk Detection","display_name":"Towards an Efficient One-Class Classifier for Mobile Devices and Wearable Sensors on the Context of Personal Risk Detection","publication_year":2018,"publication_date":"2018-08-30","ids":{"openalex":"https://openalex.org/W2888870618","doi":"https://doi.org/10.3390/s18092857","mag":"2888870618","pmid":"https://pubmed.ncbi.nlm.nih.gov/30200188"},"language":"en","primary_location":{"id":"doi:10.3390/s18092857","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s18092857","pdf_url":"https://www.mdpi.com/1424-8220/18/9/2857/pdf?version=1535712159","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/18/9/2857/pdf?version=1535712159","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011568579","display_name":"Luis A. Trejo","orcid":"https://orcid.org/0000-0001-9741-4581"},"institutions":[{"id":"https://openalex.org/I98461037","display_name":"Tecnol\u00f3gico de Monterrey","ror":"https://ror.org/03ayjn504","country_code":"MX","type":"education","lineage":["https://openalex.org/I98461037"]}],"countries":["MX"],"is_corresponding":true,"raw_author_name":"Luis Trejo","raw_affiliation_strings":["Tecnologico de Monterrey, Escuela de Ingenier\u00eda y Ciencias, Carretera al Lago de Guadalupe Km. 3.5, Atizap\u00e1n, Edo. de M\u00e9xico C.P. 52926, Mexico"],"raw_orcid":"https://orcid.org/0000-0001-9741-4581","affiliations":[{"raw_affiliation_string":"Tecnologico de Monterrey, Escuela de Ingenier\u00eda y Ciencias, Carretera al Lago de Guadalupe Km. 3.5, Atizap\u00e1n, Edo. de M\u00e9xico C.P. 52926, Mexico","institution_ids":["https://openalex.org/I98461037"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075714432","display_name":"Ari Yair Barrera-Animas","orcid":"https://orcid.org/0000-0002-8533-125X"},"institutions":[{"id":"https://openalex.org/I98461037","display_name":"Tecnol\u00f3gico de Monterrey","ror":"https://ror.org/03ayjn504","country_code":"MX","type":"education","lineage":["https://openalex.org/I98461037"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Ari Barrera-Animas","raw_affiliation_strings":["Tecnologico de Monterrey, Escuela de Ingenier\u00eda y Ciencias, Carretera al Lago de Guadalupe Km. 3.5, Atizap\u00e1n, Edo. de M\u00e9xico C.P. 52926, Mexico"],"raw_orcid":"https://orcid.org/0000-0002-8533-125X","affiliations":[{"raw_affiliation_string":"Tecnologico de Monterrey, Escuela de Ingenier\u00eda y Ciencias, Carretera al Lago de Guadalupe Km. 3.5, Atizap\u00e1n, Edo. de M\u00e9xico C.P. 52926, Mexico","institution_ids":["https://openalex.org/I98461037"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5011568579"],"corresponding_institution_ids":["https://openalex.org/I98461037"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":0.5535,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.76619242,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"18","issue":"9","first_page":"2857","last_page":"2857"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.979200005531311,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9681000113487244,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computer-science","display_name":"Computer science","score":0.8076604604721069},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6825460195541382},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6420527100563049},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.6038314700126648},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5610090494155884},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5545644760131836},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.465177983045578},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4423716068267822},{"id":"https://openalex.org/keywords/wearable-technology","display_name":"Wearable technology","score":0.43555495142936707},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42229267954826355},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4195817708969116},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41266652941703796},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3694714903831482}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8076604604721069},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6825460195541382},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6420527100563049},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.6038314700126648},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5610090494155884},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5545644760131836},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.465177983045578},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4423716068267822},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.43555495142936707},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42229267954826355},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4195817708969116},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41266652941703796},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3694714903831482},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000076251","descriptor_name":"Wearable Electronic Devices","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000076251","descriptor_name":"Wearable Electronic Devices","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000076251","descriptor_name":"Wearable Electronic Devices","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018570","descriptor_name":"Risk Assessment","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D018570","descriptor_name":"Risk Assessment","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D018570","descriptor_name":"Risk Assessment","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D025341","descriptor_name":"Principal Component Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D025341","descriptor_name":"Principal Component Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D025341","descriptor_name":"Principal Component Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D040421","descriptor_name":"Cell Phone","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D040421","descriptor_name":"Cell Phone","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D040421","descriptor_name":"Cell Phone","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D055815","descriptor_name":"Young Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055815","descriptor_name":"Young Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055815","descriptor_name":"Young Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":6,"locations":[{"id":"doi:10.3390/s18092857","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s18092857","pdf_url":"https://www.mdpi.com/1424-8220/18/9/2857/pdf?version=1535712159","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:30200188","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30200188","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:europepmc.org:5126088","is_oa":true,"landing_page_url":"http://europepmc.org/pmc/articles/PMC6163624","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"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":"","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:6163624","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6163624","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:b810e0c54ec14f32ae99615859c464ed","is_oa":true,"landing_page_url":"https://doaj.org/article/b810e0c54ec14f32ae99615859c464ed","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 18, Iss 9, p 2857 (2018)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/18/9/2857/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/s18092857","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s18092857","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s18092857","pdf_url":"https://www.mdpi.com/1424-8220/18/9/2857/pdf?version=1535712159","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320323037","display_name":"Instituto Tecnol\u00f3gico y de Estudios Superiores de Monterrey","ror":"https://ror.org/03ayjn504"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2888870618.pdf","grobid_xml":"https://content.openalex.org/works/W2888870618.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1565746575","https://openalex.org/W1872773245","https://openalex.org/W2001141328","https://openalex.org/W2053186076","https://openalex.org/W2057968074","https://openalex.org/W2111460811","https://openalex.org/W2127613611","https://openalex.org/W2146291834","https://openalex.org/W2153635508","https://openalex.org/W2170085298","https://openalex.org/W2253420670","https://openalex.org/W2283153737","https://openalex.org/W2341782166","https://openalex.org/W2343960176","https://openalex.org/W2493175080","https://openalex.org/W2525640029","https://openalex.org/W2749720859","https://openalex.org/W2770641139","https://openalex.org/W2803242616","https://openalex.org/W3099514962","https://openalex.org/W6696208799"],"related_works":["https://openalex.org/W3090300519","https://openalex.org/W2514492205","https://openalex.org/W4250401876","https://openalex.org/W2943851981","https://openalex.org/W2566526749","https://openalex.org/W2907667791","https://openalex.org/W3047461507","https://openalex.org/W3126390843","https://openalex.org/W4245880644","https://openalex.org/W2481123202"],"abstract_inverted_index":{"In":[0],"this":[1,160],"work,":[2],"we":[3,164],"present":[4],"a":[5,24,86,110,117,123,129,176,206,220,225,307,321,341],"first":[6,70],"step":[7],"towards":[8],"an":[9,92,277],"efficient":[10],"one-class":[11,40],"classifier":[12,328],"well":[13,144],"suited":[14],"for":[15,268,306],"mobile":[16,308],"devices":[17],"to":[18,257],"be":[19],"implemented":[20],"as":[21,143,145,300],"part":[22],"of":[23,34,60,94,112,140,189,199,208,227,232,236,298],"user":[25],"application":[26],"coupled":[27],"with":[28,49,98],"wearable":[29],"sensors":[30],"in":[31,101,159,216,247,265,279,284],"the":[32,61,73,95,102,138,141,147,151,172,192,196,217,228,233,252,280,286,296,327,332],"context":[33],"personal":[35],"risk":[36],"detection.":[37],"We":[38,84],"compared":[39],"Support":[41],"Vector":[42],"Machine":[43],"(ocSVM)":[44],"and":[45,153,201,291,313],"OCKRA":[46,184,214,299,319],"(One-Class":[47],"K-means":[48],"Randomly-projected":[50],"features":[51,200],"Algorithm).":[52],"Both":[53],"classifiers":[54,142],"were":[55,135],"tested":[56],"using":[57,195,205,224,331],"four":[58],"versions":[59],"publicly":[62],"available":[63],"PRIDE":[64,75,333],"(Personal":[65],"RIsk":[66],"DEtection)":[67],"dataset.":[68],"The":[69,105],"version":[71,88],"is":[72,78,90,162],"original":[74,96],"dataset,":[76],"which":[77,248],"based":[79,121,335],"only":[80,336],"on":[81,122,137,146,186,337],"time-domain":[82,338],"features.":[83,237],"created":[85],"second":[87],"that":[89,183],"simply":[91],"extension":[93],"dataset":[97,334],"new":[99],"attributes":[100,339],"frequency":[103],"domain.":[104],"other":[106],"two":[107,114],"datasets":[108],"are":[109,240,254,262,316],"subset":[111,207,226],"these":[113],"versions,":[115],"after":[116,340],"feature":[118,229,342],"selection":[119,343],"procedure":[120],"correlation":[124],"matrix":[125],"analysis":[126],"followed":[127],"by":[128,245],"Principal":[130],"Component":[131],"Analysis.":[132],"All":[133],"experiments":[134],"focused":[136],"performance":[139,290,329],"execution":[148,168,212,260],"time":[149,169,174],"during":[150],"training":[152],"classification":[154,178,289],"processes.":[155],"Therefore,":[156],"our":[157,293,301],"goal":[158],"work":[161],"twofold:":[163],"aim":[165],"at":[166,171,317],"reducing":[167],"but":[170],"same":[173],"maintaining":[175],"good":[177],"performance.":[179],"Our":[180],"results":[181,239,294],"show":[182],"achieved":[185],"average,":[187],"89.1%":[188],"Area":[190],"Under":[191],"Curve":[193],"(AUC)":[194],"full":[197,234],"set":[198,235],"83.7%":[202],"when":[203,223,330],"trained":[204],"them.":[209],"Furthermore,":[210],"regarding":[211],"time,":[213],"reports":[215,320],"best":[218,302],"case":[219],"33.1%":[221],"gain":[222],"vector,":[230],"instead":[231],"These":[238],"better":[241],"than":[242,271,276],"those":[243],"reported":[244],"ocSVM,":[246],"case,":[249],"even":[250],"though":[251],"AUCs":[253],"very":[255,322],"close":[256],"each":[258],"other,":[259],"times":[261],"significantly":[263],"higher":[264],"all":[266],"cases,":[267],"example,":[269],"more":[270],"20":[272],"h":[273],"versus":[274],"less":[275,311],"hour":[278],"worst-case":[281],"scenario.":[282],"Having":[283],"mind":[285],"trade-off":[287],"between":[288],"efficiency,":[292],"support":[295],"choice":[297],"candidate":[303],"so":[304],"far":[305],"implementation":[309],"where":[310],"processing":[312],"memory":[314],"resources":[315],"hand.":[318],"encouraging":[323],"speed-up":[324],"without":[325],"sacrificing":[326],"procedure.":[344]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}