{"id":"https://openalex.org/W7168360322","doi":"https://doi.org/10.5753/jbcs.2026.7346","title":"Efficient and Fast Kolmogorov\u2013Arnold Networks for Chest X-Ray Classification of Pneumonia and Tuberculosis","display_name":"Efficient and Fast Kolmogorov\u2013Arnold Networks for Chest X-Ray Classification of Pneumonia and Tuberculosis","publication_year":2026,"publication_date":"2026-07-10","ids":{"openalex":"https://openalex.org/W7168360322","doi":"https://doi.org/10.5753/jbcs.2026.7346"},"language":null,"primary_location":{"id":"doi:10.5753/jbcs.2026.7346","is_oa":true,"landing_page_url":"https://doi.org/10.5753/jbcs.2026.7346","pdf_url":"https://journals-sol.sbc.org.br/index.php/jbcs/article/download/7346/4151","source":{"id":"https://openalex.org/S69801987","display_name":"Journal of the Brazilian Computer Society","issn_l":"0104-6500","issn":["0104-6500","1678-4804"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Brazilian Computer Society","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journals-sol.sbc.org.br/index.php/jbcs/article/download/7346/4151","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140873545","display_name":"Alexsander Lindolfo De Lima","orcid":"https://orcid.org/0000-0002-9865-2781"},"institutions":[{"id":"https://openalex.org/I80850581","display_name":"Universidade Federal de Uberl\u00e2ndia","ror":"https://ror.org/04x3wvr31","country_code":"BR","type":"education","lineage":["https://openalex.org/I80850581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Alexsander Lindolfo De Lima","raw_affiliation_strings":["Federal University of Uberlandia"],"raw_orcid":"https://orcid.org/0000-0002-9865-2781","affiliations":[{"raw_affiliation_string":"Federal University of Uberlandia","institution_ids":["https://openalex.org/I80850581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140958615","display_name":"Henrique Fernandes","orcid":"https://orcid.org/0000-0002-7078-9620"},"institutions":[{"id":"https://openalex.org/I80850581","display_name":"Universidade Federal de Uberl\u00e2ndia","ror":"https://ror.org/04x3wvr31","country_code":"BR","type":"education","lineage":["https://openalex.org/I80850581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Henrique Fernandes","raw_affiliation_strings":["Federal University of Uberl\u00e2ndia"],"raw_orcid":"https://orcid.org/0000-0002-7078-9620","affiliations":[{"raw_affiliation_string":"Federal University of Uberl\u00e2ndia","institution_ids":["https://openalex.org/I80850581"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5140935276","display_name":"Jose dos Reis V. Moura Junior","orcid":"https://orcid.org/0000-0002-8701-8355"},"institutions":[{"id":"https://openalex.org/I80850581","display_name":"Universidade Federal de Uberl\u00e2ndia","ror":"https://ror.org/04x3wvr31","country_code":"BR","type":"education","lineage":["https://openalex.org/I80850581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Jose dos Reis V. Moura Junior","raw_affiliation_strings":["Federal University of Uberlandia"],"raw_orcid":"https://orcid.org/0000-0002-8701-8355","affiliations":[{"raw_affiliation_string":"Federal University of Uberlandia","institution_ids":["https://openalex.org/I80850581"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I80850581"],"apc_list":{"value":1390,"currency":"USD","value_usd":1390},"apc_paid":{"value":1390,"currency":"USD","value_usd":1390},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.75917021,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"32","issue":"1","first_page":"1850","last_page":"1858"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9783999919891357,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9783999919891357,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.001500000013038516,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.0010000000474974513,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8043000102043152},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.541100025177002},{"id":"https://openalex.org/keywords/pneumonia","display_name":"Pneumonia","score":0.5270000100135803},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5060999989509583},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.46149998903274536},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.4357999861240387},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3837999999523163},{"id":"https://openalex.org/keywords/tuberculosis","display_name":"Tuberculosis","score":0.37560001015663147}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8043000102043152},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7032999992370605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5425999760627747},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.541100025177002},{"id":"https://openalex.org/C2777914695","wikidata":"https://www.wikidata.org/wiki/Q12192","display_name":"Pneumonia","level":2,"score":0.5270000100135803},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5060999989509583},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.46149998903274536},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45809999108314514},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4357999861240387},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3837999999523163},{"id":"https://openalex.org/C2781069245","wikidata":"https://www.wikidata.org/wiki/Q12204","display_name":"Tuberculosis","level":2,"score":0.37560001015663147},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3628000020980835},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.3393999934196472},{"id":"https://openalex.org/C3020132585","wikidata":"https://www.wikidata.org/wiki/Q2671652","display_name":"Diagnostic accuracy","level":2,"score":0.33149999380111694},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3158999979496002},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.3091999888420105},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2858000099658966},{"id":"https://openalex.org/C2779549770","wikidata":"https://www.wikidata.org/wiki/Q1122413","display_name":"Computer-aided diagnosis","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2603999972343445},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.25769999623298645},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5753/jbcs.2026.7346","is_oa":true,"landing_page_url":"https://doi.org/10.5753/jbcs.2026.7346","pdf_url":"https://journals-sol.sbc.org.br/index.php/jbcs/article/download/7346/4151","source":{"id":"https://openalex.org/S69801987","display_name":"Journal of the Brazilian Computer Society","issn_l":"0104-6500","issn":["0104-6500","1678-4804"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Brazilian Computer Society","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.5753/jbcs.2026.7346","is_oa":true,"landing_page_url":"https://doi.org/10.5753/jbcs.2026.7346","pdf_url":"https://journals-sol.sbc.org.br/index.php/jbcs/article/download/7346/4151","source":{"id":"https://openalex.org/S69801987","display_name":"Journal of the Brazilian Computer Society","issn_l":"0104-6500","issn":["0104-6500","1678-4804"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Brazilian Computer Society","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.5270807147026062}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7168360322.pdf","grobid_xml":"https://content.openalex.org/works/W7168360322.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W1558233590","https://openalex.org/W1976863970","https://openalex.org/W2112796928","https://openalex.org/W2137983211","https://openalex.org/W2323929895","https://openalex.org/W2788633781","https://openalex.org/W2904335605","https://openalex.org/W2949301588","https://openalex.org/W2957177432","https://openalex.org/W2993464084","https://openalex.org/W2994429299","https://openalex.org/W3045801508","https://openalex.org/W3112390123","https://openalex.org/W4238143865","https://openalex.org/W4308160156","https://openalex.org/W4312320913","https://openalex.org/W4387806602","https://openalex.org/W4388492864","https://openalex.org/W4391824793","https://openalex.org/W4392173803","https://openalex.org/W4394601976","https://openalex.org/W4396689305","https://openalex.org/W4396878152","https://openalex.org/W4398159307","https://openalex.org/W4399999567","https://openalex.org/W4400421906","https://openalex.org/W4402659198","https://openalex.org/W4404916195","https://openalex.org/W4405002043","https://openalex.org/W4406308687","https://openalex.org/W4407450210","https://openalex.org/W4408779320","https://openalex.org/W4411095744","https://openalex.org/W4412947400","https://openalex.org/W4413179843","https://openalex.org/W4413449500","https://openalex.org/W7126024841","https://openalex.org/W7134200130","https://openalex.org/W7135387357","https://openalex.org/W7162683220"],"related_works":[],"abstract_inverted_index":{"Interpreting":[0],"chest":[1,81],"X-ray":[2,82],"images":[3,83],"can":[4],"be":[5],"challenging,":[6],"leading":[7],"to":[8,17,71,118],"an":[9,54],"increasing":[10],"reliance":[11],"on":[12],"computational":[13,131],"methods":[14],"by":[15],"physicians":[16],"improve":[18],"diagnostic":[19],"accuracy":[20,123],"and":[21,61,96,102,142,148],"disease":[22],"monitoring.":[23],"Among":[24],"these":[25],"methods,":[26],"machine":[27],"learning":[28],"models\u2014particularly":[29],"those":[30],"in":[31,43,124],"computer":[32],"vision,":[33],"such":[34],"as":[35,53,85],"Convolutional":[36],"Neural":[37],"Networks":[38,49],"(CNNs)\u2014have":[39],"shown":[40],"strong":[41],"performance":[42,116],"image":[44,153],"classification":[45,74],"tasks.":[46],"Recently,":[47],"Kolmogorov-Arnold":[48],"(KANs)":[50],"have":[51],"emerged":[52],"alternative":[55],"framework":[56],"that":[57,111,139],"redefines":[58],"how":[59],"connections":[60],"activations":[62],"are":[63,145],"computed":[64],"within":[65],"neural":[66],"architectures.":[67],"This":[68],"study":[69],"aims":[70],"develop":[72],"a":[73,77,105,129,146],"system":[75],"using":[76],"dataset":[78],"of":[79,133],"5,000":[80],"categorized":[84],"Normal,":[86],"Pneumonia,":[87],"or":[88],"Tuberculosis.":[89],"Two":[90],"KAN-based":[91],"algorithms,":[92],"Efficient":[93],"KAN":[94,98],"(EKAN)":[95],"Fast":[97],"(FKAN),":[99],"were":[100],"implemented":[101],"compared":[103],"with":[104,120,128],"CNN":[106,119],"baseline.":[107],"Experimental":[108],"results":[109,137],"show":[110],"the":[112,140],"FKAN":[113,141],"model":[114],"achieved":[115],"comparable":[117],"approximately":[121,134],"96%":[122],"test":[125],"cases,":[126],"but":[127],"reduced":[130],"cost":[132],"96.18%.":[135],"The":[136],"suggest":[138],"EKAN":[143],"algorithms":[144],"practical":[147],"efficient":[149],"approach":[150],"for":[151],"medical":[152],"classification.":[154]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2026-07-16T00:00:00"}
