{"id":"https://openalex.org/W3139016750","doi":"https://doi.org/10.1109/bigdata50022.2020.9377780","title":"Automated Machine Learning for the Classification of Normal and Abnormal Electromyography Data","display_name":"Automated Machine Learning for the Classification of Normal and Abnormal Electromyography Data","publication_year":2020,"publication_date":"2020-12-10","ids":{"openalex":"https://openalex.org/W3139016750","doi":"https://doi.org/10.1109/bigdata50022.2020.9377780","mag":"3139016750"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata50022.2020.9377780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9377780","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://scholarlypublications.universiteitleiden.nl/access/item%3A3763938/view","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009107086","display_name":"Marios Kefalas","orcid":"https://orcid.org/0000-0002-2422-758X"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Marios Kefalas","raw_affiliation_strings":["Leiden University, Leiden, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Leiden University, Leiden, The Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018227516","display_name":"Milan Koch","orcid":null},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Milan Koch","raw_affiliation_strings":["Leiden University, Leiden, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Leiden University, Leiden, The Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047027035","display_name":"Victor J. Geraedts","orcid":"https://orcid.org/0000-0002-6604-8707"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Victor Geraedts","raw_affiliation_strings":["Leiden University, Leiden, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Leiden University, Leiden, The Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100655167","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0002-1089-9828"},"institutions":[{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Hao Wang","raw_affiliation_strings":["Sorbonne Universit\u00e9, Paris, France"],"affiliations":[{"raw_affiliation_string":"Sorbonne Universit\u00e9, Paris, France","institution_ids":["https://openalex.org/I39804081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002314394","display_name":"Martijn R. Tannemaat","orcid":"https://orcid.org/0000-0003-2929-0390"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Martijn Tannemaat","raw_affiliation_strings":["Leiden University, Leiden, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Leiden University, Leiden, The Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062646838","display_name":"Thomas B\u00e4ck","orcid":"https://orcid.org/0000-0001-6768-1478"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Thomas Back","raw_affiliation_strings":["Leiden University, Leiden, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Leiden University, Leiden, The Netherlands","institution_ids":["https://openalex.org/I121797337"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5009107086"],"corresponding_institution_ids":["https://openalex.org/I121797337"],"apc_list":null,"apc_paid":null,"fwci":0.2605,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.53126118,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1176","last_page":"1185"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9514999985694885,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/electromyography","display_name":"Electromyography","score":0.8074959516525269},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5653289556503296},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5566952228546143},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5171343684196472},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4951306879520416},{"id":"https://openalex.org/keywords/neurophysiology","display_name":"Neurophysiology","score":0.4777714014053345},{"id":"https://openalex.org/keywords/myopathy","display_name":"Myopathy","score":0.4706769585609436},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.464474081993103},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45943304896354675},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4027402997016907},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.38403084874153137},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.34755462408065796},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.1565864086151123}],"concepts":[{"id":"https://openalex.org/C2777515770","wikidata":"https://www.wikidata.org/wiki/Q507369","display_name":"Electromyography","level":2,"score":0.8074959516525269},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5653289556503296},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5566952228546143},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5171343684196472},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4951306879520416},{"id":"https://openalex.org/C152478114","wikidata":"https://www.wikidata.org/wiki/Q660910","display_name":"Neurophysiology","level":2,"score":0.4777714014053345},{"id":"https://openalex.org/C2777300911","wikidata":"https://www.wikidata.org/wiki/Q692536","display_name":"Myopathy","level":2,"score":0.4706769585609436},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.464474081993103},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45943304896354675},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4027402997016907},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.38403084874153137},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.34755462408065796},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.1565864086151123},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata50022.2020.9377780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9377780","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:scholarlypublications.universiteitleiden.nl:item_3763937","is_oa":true,"landing_page_url":"https://hdl.handle.net/1887/3763937","pdf_url":"https://scholarlypublications.universiteitleiden.nl/access/item%3A3763938/view","source":{"id":"https://openalex.org/S4306400850","display_name":"Leiden Repository (Leiden University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I121797337","host_organization_name":"Leiden University","host_organization_lineage":["https://openalex.org/I121797337"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"Article in monograph or in proceedings"}],"best_oa_location":{"id":"pmh:oai:scholarlypublications.universiteitleiden.nl:item_3763937","is_oa":true,"landing_page_url":"https://hdl.handle.net/1887/3763937","pdf_url":"https://scholarlypublications.universiteitleiden.nl/access/item%3A3763938/view","source":{"id":"https://openalex.org/S4306400850","display_name":"Leiden Repository (Leiden University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I121797337","host_organization_name":"Leiden University","host_organization_lineage":["https://openalex.org/I121797337"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"Article in monograph or in proceedings"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W3139016750.pdf"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1963544390","https://openalex.org/W1969935486","https://openalex.org/W1974416347","https://openalex.org/W2002542906","https://openalex.org/W2010779658","https://openalex.org/W2012510034","https://openalex.org/W2014899819","https://openalex.org/W2017654378","https://openalex.org/W2022319257","https://openalex.org/W2060093283","https://openalex.org/W2079409030","https://openalex.org/W2105723190","https://openalex.org/W2123167643","https://openalex.org/W2140404878","https://openalex.org/W2148143831","https://openalex.org/W2148154913","https://openalex.org/W2156665896","https://openalex.org/W2409983459","https://openalex.org/W2485709337","https://openalex.org/W2545001194","https://openalex.org/W2773031903","https://openalex.org/W2802314367","https://openalex.org/W2897127292","https://openalex.org/W2897375082","https://openalex.org/W2908646035","https://openalex.org/W2976180054","https://openalex.org/W3008027773","https://openalex.org/W4233328230","https://openalex.org/W4298188449","https://openalex.org/W6680531176","https://openalex.org/W6729149246","https://openalex.org/W6843302958"],"related_works":["https://openalex.org/W2376139493","https://openalex.org/W2911808920","https://openalex.org/W2141253262","https://openalex.org/W3156756500","https://openalex.org/W4251090744","https://openalex.org/W2386293158","https://openalex.org/W1531884930","https://openalex.org/W2015558867","https://openalex.org/W2155452364","https://openalex.org/W2886903279"],"abstract_inverted_index":{"Needle":[0],"electromyography":[1],"(EMG)":[2],"is":[3,60,71,226],"a":[4,149,166,179,220,223],"common":[5],"technique":[6,151],"used":[7,26],"in":[8,51,108,127,178,185,217],"clinical":[9],"neurophysiology":[10],"to":[11,27,76,94,182],"record":[12],"the":[13,33,49,101,129,137,141,144,155,160,171,174],"electrical":[14],"activity":[15],"of":[16,21,36,57,83,103,106,118,143,154,173,204],"muscles":[17,107],"at":[18],"different":[19],"levels":[20],"activation.":[22],"It":[23],"can":[24,214],"be":[25],"diagnose":[28],"various":[29],"neurological/muscular":[30],"disorders,":[31],"as":[32,68,152],"EMG":[34,80,104],"signals":[35],"patients":[37,184],"with":[38,87],"both":[39],"nerve":[40],"diseases":[41,45],"(neuropathies)":[42],"and":[43,67,74,89,125,140,207],"muscle":[44,194],"(myopathies)":[46],"differ":[47],"from":[48,136,159],"signal":[50],"healthy":[52,112],"controls.":[53],"A":[54],"major":[55],"drawback":[56],"this":[58],"examination":[59],"that":[61,211],"it":[62,70],"relies":[63],"on":[64,79,192],"visual":[65],"inspection":[66],"such,":[69],"highly":[72],"subjective":[73],"prone":[75],"errors.":[77],"Based":[78],"time":[81],"series":[82],"65":[84],"individuals":[85],"(40":[86],"ALS/IBM":[88],"25":[90],"healthy),":[91],"we":[92,163],"aim":[93],"develop":[95],"an":[96,201],"automated":[97,115,156,176],"machine-learning":[98],"pipeline":[99,116,177],"for":[100],"classification":[102],"recordings":[105],"either":[109,187],"disease":[110,188],"or":[111,189,225],"(muscle-level).":[113],"The":[114,196],"consists":[117],"feature":[119,121,138],"extraction,":[120],"selection,":[122],"modelling":[123],"algorithm,":[124],"optimization,":[126],"which":[128,169],"most":[130],"significant":[131],"features":[132],"are":[133,146],"automatically":[134],"selected":[135],"space":[139],"hyperparameters":[142],"model":[145],"optimized":[147],"by":[148],"Bayesian":[150],"part":[153],"approach.":[157],"Aside":[158],"muscle-level":[161,175],"approach,":[162,168],"also":[164],"explore":[165],"patient-level":[167],"uses":[170],"output":[172],"post-processing":[180],"manner":[181],"classify":[183],"being":[186],"healthy,":[190],"based":[191],"their":[193],"recordings.":[195],"resulting":[197],"two":[198],"approaches":[199,213],"yield":[200],"AUC":[202],"score":[203],"81.7%":[205],"(muscle-level)":[206],"81.5%":[208],"(patient-level),":[209],"indicating":[210],"such":[212],"assist":[215],"clinicians":[216],"diagnosing":[218],"if":[219],"patient":[221],"has":[222],"neuropathy/myopathy":[224],"healthy.":[227]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-26T15:22:09.906841","created_date":"2025-10-10T00:00:00"}
