{"id":"https://openalex.org/W4410341735","doi":"https://doi.org/10.1109/ncc63735.2025.10983200","title":"A Machine Learning Approach for Idiopathic Ventricular Arrhythmia Source Classification","display_name":"A Machine Learning Approach for Idiopathic Ventricular Arrhythmia Source Classification","publication_year":2025,"publication_date":"2025-03-06","ids":{"openalex":"https://openalex.org/W4410341735","doi":"https://doi.org/10.1109/ncc63735.2025.10983200"},"language":"en","primary_location":{"id":"doi:10.1109/ncc63735.2025.10983200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncc63735.2025.10983200","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 National Conference on Communications (NCC)","raw_type":"proceedings-article"},"type":"article","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/A5047056773","display_name":"Sibasankar Padhy","orcid":"https://orcid.org/0000-0001-9131-1004"},"institutions":[{"id":"https://openalex.org/I4210152718","display_name":"Indian Institute of Technology Dharwad","ror":"https://ror.org/0509djg30","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210152718"]},{"id":"https://openalex.org/I26072440","display_name":"Indian Institute of Information Technology Allahabad","ror":"https://ror.org/03rgjt374","country_code":"IN","type":"education","lineage":["https://openalex.org/I26072440"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Sibasankar Padhy","raw_affiliation_strings":["Indian Institute of Information Technology,Department of Electronics and Communication Engineering,Dharwad,Karnataka,India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Information Technology,Department of Electronics and Communication Engineering,Dharwad,Karnataka,India","institution_ids":["https://openalex.org/I4210152718","https://openalex.org/I26072440"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5047056773"],"corresponding_institution_ids":["https://openalex.org/I26072440","https://openalex.org/I4210152718"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21946255,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9478999972343445,"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.9478999972343445,"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/computer-science","display_name":"Computer science","score":0.6493226289749146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5336599349975586},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45937642455101013}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6493226289749146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5336599349975586},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45937642455101013}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ncc63735.2025.10983200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncc63735.2025.10983200","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 National Conference on Communications (NCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1712564456","https://openalex.org/W2000926512","https://openalex.org/W2000982976","https://openalex.org/W2005208134","https://openalex.org/W2063096929","https://openalex.org/W2076723282","https://openalex.org/W2114972926","https://openalex.org/W2123785188","https://openalex.org/W2142799840","https://openalex.org/W2461472189","https://openalex.org/W2774819460","https://openalex.org/W2899278391","https://openalex.org/W2958872067","https://openalex.org/W3012694898","https://openalex.org/W4318053935","https://openalex.org/W4400042612"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"The":[0,122],"study":[1,87],"of":[2,43,71,129,131,141,158,171],"idiopathic":[3],"ventricular":[4,10,14,58,65],"arrhythmias":[5],"(IVAs),":[6],"associated":[7],"with":[8,179],"premature":[9],"contractions":[11],"(PVCs)":[12],"and":[13,62,119,135,149,156,162,185],"tachycardia":[15],"(VT),":[16],"has":[17],"a":[18,89,139],"significant":[19],"focus":[20],"in":[21,40,133],"clinical":[22],"research":[23],"as":[24],"they":[25],"may":[26],"escalate":[27],"into":[28],"serious":[29],"health":[30],"conditions,":[31],"including":[32],"sudden":[33],"cardiac":[34],"arrest.":[35],"These":[36,166],"arrhythmias,":[37],"which":[38],"occur":[39],"the":[41,56,63,126,144,169],"absence":[42],"structural":[44],"heart":[45],"disease,":[46],"can":[47],"often":[48],"be":[49],"traced":[50],"to":[51],"two":[52],"primary":[53],"anatomical":[54],"regions:":[55],"right":[57],"outflow":[59,66],"tract":[60,67],"(RVOT)":[61],"left":[64],"(LVOT).":[68],"Proper":[69],"classification":[70,92],"these":[72],"origins":[73],"is":[74,84],"critical":[75],"for":[76,94,175,181],"guiding":[77],"treatment":[78],"decisions,":[79],"particularly":[80],"when":[81],"catheter":[82],"ablation":[83,188],"considered.":[85],"This":[86],"proposes":[88],"machine":[90],"learning-based":[91],"model":[93,146],"identifying":[95],"IVA":[96,176,183],"sources":[97],"using":[98],"12-lead":[99],"ECG":[100,107,173],"data.":[101],"Key":[102],"features":[103,124],"were":[104],"extracted":[105,123],"from":[106],"signals":[108],"through":[109],"multivariate":[110],"variational":[111],"mode":[112],"decomposition":[113],"(MVMD),":[114],"phase-rectified":[115],"signal":[116],"averaging":[117],"(PRSA),":[118],"mobility-complexity":[120],"features.":[121],"demonstrated":[125],"distinguishing":[127],"capability":[128],"origin":[130],"IVAs":[132],"RVOT":[134],"LVOT.":[136],"Evaluated":[137],"on":[138],"dataset":[140],"334":[142],"patients,":[143],"proposed":[145],"used":[147],"SVM":[148],"achieved":[150],"an":[151],"average":[152],"sensitivity,":[153],"specificity,":[154],"accuracy,":[155],"F-score":[157],"79.7%,":[159],"80.8%,":[160],"78.4%,":[161],"77.1":[163],"%,":[164],"respectively.":[165],"findings":[167],"demonstrate":[168],"potential":[170],"automated":[172],"analysis":[174],"source":[177],"classification,":[178],"implications":[180],"enhancing":[182],"diagnostics":[184],"informing":[186],"targeted":[187],"treatments.":[189]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
