{"id":"https://openalex.org/W2342624423","doi":"https://doi.org/10.1109/healthcom.2015.7454509","title":"Multi-level classification: A generic classification method for medical datasets","display_name":"Multi-level classification: A generic classification method for medical datasets","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2342624423","doi":"https://doi.org/10.1109/healthcom.2015.7454509","mag":"2342624423"},"language":"en","primary_location":{"id":"doi:10.1109/healthcom.2015.7454509","is_oa":false,"landing_page_url":"https://doi.org/10.1109/healthcom.2015.7454509","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 17th International Conference on E-health Networking, Application &amp; Services (HealthCom)","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/A5112396202","display_name":"M. Srinivas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M Srinivas","raw_affiliation_strings":["VIsual learninG and InteLligence (VIGIL) group, Dept. of CSE, USA","Dept. of CSE, VIsual learninG and InteLligence (VIGIL) group"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VIsual learninG and InteLligence (VIGIL) group, Dept. of CSE, USA","institution_ids":[]},{"raw_affiliation_string":"Dept. of CSE, VIsual learninG and InteLligence (VIGIL) group","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110788594","display_name":"R Bharath","orcid":null},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R Bharath","raw_affiliation_strings":["Dept. of EE, Indian Institute of Technology Hyderabad, India","Dept. of EE, Indian Institute of Technology, Hyderabad"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of EE, Indian Institute of Technology Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]},{"raw_affiliation_string":"Dept. of EE, Indian Institute of Technology, Hyderabad","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"middle","author":{"id":null,"display_name":"P Rajalakshmi","orcid":null},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"P Rajalakshmi","raw_affiliation_strings":["Dept. of EE, Indian Institute of Technology Hyderabad, India","Dept. of EE, Indian Institute of Technology, Hyderabad"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of EE, Indian Institute of Technology Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]},{"raw_affiliation_string":"Dept. of EE, Indian Institute of Technology, Hyderabad","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012566120","display_name":"C. Krishna Mohan","orcid":"https://orcid.org/0000-0002-7316-0836"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"C Krishna Mohan","raw_affiliation_strings":["VIsual learninG and InteLligence (VIGIL) group, Dept. of CSE, USA","Dept. of CSE, VIsual learninG and InteLligence (VIGIL) group"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VIsual learninG and InteLligence (VIGIL) group, Dept. of CSE, USA","institution_ids":[]},{"raw_affiliation_string":"Dept. of CSE, VIsual learninG and InteLligence (VIGIL) group","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7807,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.89475221,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"262","last_page":"267"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9991999864578247,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9991999864578247,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9939000010490417,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9890000224113464,"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/computer-science","display_name":"Computer science","score":0.7498484253883362},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5946128368377686},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5916061997413635},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5862107872962952},{"id":"https://openalex.org/keywords/data-classification","display_name":"Data classification","score":0.5217207670211792},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5187928080558777},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5051537156105042},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.5014204978942871},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4968891441822052},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4955641031265259},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"Multiclass classification","score":0.49117347598075867},{"id":"https://openalex.org/keywords/one-class-classification","display_name":"One-class classification","score":0.4702782928943634},{"id":"https://openalex.org/keywords/linear-classifier","display_name":"Linear classifier","score":0.4411928355693817},{"id":"https://openalex.org/keywords/medical-classification","display_name":"Medical classification","score":0.41012075543403625},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18267583847045898}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7498484253883362},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5946128368377686},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5916061997413635},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5862107872962952},{"id":"https://openalex.org/C2780724565","wikidata":"https://www.wikidata.org/wiki/Q5227256","display_name":"Data classification","level":2,"score":0.5217207670211792},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5187928080558777},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5051537156105042},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.5014204978942871},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4968891441822052},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4955641031265259},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.49117347598075867},{"id":"https://openalex.org/C34872919","wikidata":"https://www.wikidata.org/wiki/Q7092302","display_name":"One-class classification","level":3,"score":0.4702782928943634},{"id":"https://openalex.org/C139532973","wikidata":"https://www.wikidata.org/wiki/Q2679259","display_name":"Linear classifier","level":3,"score":0.4411928355693817},{"id":"https://openalex.org/C154874363","wikidata":"https://www.wikidata.org/wiki/Q3518464","display_name":"Medical classification","level":2,"score":0.41012075543403625},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18267583847045898},{"id":"https://openalex.org/C159110408","wikidata":"https://www.wikidata.org/wiki/Q121176","display_name":"Nursing","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/healthcom.2015.7454509","is_oa":false,"landing_page_url":"https://doi.org/10.1109/healthcom.2015.7454509","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 17th International Conference on E-health Networking, Application &amp; Services (HealthCom)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1514182922","https://openalex.org/W1583988398","https://openalex.org/W1969557815","https://openalex.org/W1976597329","https://openalex.org/W1981097774","https://openalex.org/W1981424282","https://openalex.org/W1981653086","https://openalex.org/W1983293294","https://openalex.org/W1992405901","https://openalex.org/W2000077229","https://openalex.org/W2002964621","https://openalex.org/W2005876975","https://openalex.org/W2009414485","https://openalex.org/W2013189015","https://openalex.org/W2029395046","https://openalex.org/W2054071230","https://openalex.org/W2075303515","https://openalex.org/W2082967391","https://openalex.org/W2093461052","https://openalex.org/W2096141173","https://openalex.org/W2096780489","https://openalex.org/W2107373450","https://openalex.org/W2108986847","https://openalex.org/W2115429828","https://openalex.org/W2131807627","https://openalex.org/W2133485604","https://openalex.org/W2137511707","https://openalex.org/W2151693816","https://openalex.org/W2156909104","https://openalex.org/W2158404716","https://openalex.org/W2160547390","https://openalex.org/W2161896700","https://openalex.org/W2167826084","https://openalex.org/W3120740533","https://openalex.org/W6630666109","https://openalex.org/W6674791568","https://openalex.org/W6679241744"],"related_works":["https://openalex.org/W1734803745","https://openalex.org/W2584344423","https://openalex.org/W4376528628","https://openalex.org/W1921594662","https://openalex.org/W2121692343","https://openalex.org/W2048202529","https://openalex.org/W2998259334","https://openalex.org/W2974328778","https://openalex.org/W2342624423","https://openalex.org/W2249455904"],"abstract_inverted_index":{"Classification":[0],"of":[1,6,53,106,141],"medical":[2,25,58,83,135],"data":[3,39,115],"is":[4,20],"one":[5],"the":[7,50,99,131,139,142],"most":[8],"challenging":[9],"pattern":[10],"recognition":[11],"problems.":[12],"As":[13],"stated":[14],"in":[15,57,72,124],"literature":[16],"a":[17,77],"single":[18],"classifier":[19],"unable":[21],"to":[22,30,33,48,64],"solve":[23,49],"all":[24,61,110],"image":[26],"classification":[27,54,80,107,145],"problems":[28,55,116],"due":[29],"high":[31],"sensitivity":[32],"noise":[34],"and":[35,90,121],"other":[36],"imperfections":[37],"like":[38],"imbalance.":[40],"So,":[41],"several":[42],"individual":[43],"classifiers":[44],"have":[45,62],"been":[46],"studied":[47],"different":[51],"types":[52],"arising":[56],"datasets":[59,84,111,136],"but":[60],"proven":[63],"be":[65],"useful":[66],"on":[67,130],"some":[68],"specific":[69],"datasets.":[70],"Hence,":[71],"this":[73],"paper,":[74],"we":[75],"propose":[76],"generic":[78],"multi-level":[79,125,144],"approach":[81],"for":[82],"using":[85],"sparsity":[86],"based":[87],"dictionary":[88],"learning":[89],"support":[91],"vector":[92],"machine":[93],"approaches.":[94],"The":[95,127],"proposed":[96,143],"technique":[97],"demonstrates":[98],"following":[100],"advantages:":[101],"1)":[102],"gives":[103],"better":[104],"performance":[105],"accuracy":[108],"over":[109],"2)":[112],"solves":[113],"imbalanced":[114],"3)":[117],"needs":[118],"no":[119],"fusion":[120],"ensemble":[122],"methods":[123],"classification.":[126],"results":[128],"presented":[129],"5":[132],"standard":[133],"UCI":[134],"demonstrate":[137],"that":[138],"efficacy":[140],"technique.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":43},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
