{"id":"https://openalex.org/W4413267794","doi":"https://doi.org/10.1109/access.2025.3593046","title":"IMed-CNN: Ensemble Learning Approach With Systematic Model Dropout for Enhanced Medical Image Classification Using Image Channels and Pixel Intervals","display_name":"IMed-CNN: Ensemble Learning Approach With Systematic Model Dropout for Enhanced Medical Image Classification Using Image Channels and Pixel Intervals","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4413267794","doi":"https://doi.org/10.1109/access.2025.3593046"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3593046","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3593046","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3593046","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091106383","display_name":"Javokhir Musaev","orcid":"https://orcid.org/0000-0003-4656-0479"},"institutions":[{"id":"https://openalex.org/I55240360","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159","country_code":"KR","type":"education","lineage":["https://openalex.org/I55240360"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Javokhir Musaev","raw_affiliation_strings":["Department of Computer Engineering, Yeungnam University, Gyeongsan, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-4656-0479","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Yeungnam University, Gyeongsan, South Korea","institution_ids":["https://openalex.org/I55240360"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084255344","display_name":"Abdulaziz Anorboev","orcid":"https://orcid.org/0000-0003-1416-7138"},"institutions":[{"id":"https://openalex.org/I55240360","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159","country_code":"KR","type":"education","lineage":["https://openalex.org/I55240360"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Abdulaziz Anorboev","raw_affiliation_strings":["Department of Computer Engineering, Yeungnam University, Gyeongsan, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-1416-7138","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Yeungnam University, Gyeongsan, South Korea","institution_ids":["https://openalex.org/I55240360"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012219094","display_name":"Yeong\u2010Seok Seo","orcid":"https://orcid.org/0000-0002-5319-7674"},"institutions":[{"id":"https://openalex.org/I55240360","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159","country_code":"KR","type":"education","lineage":["https://openalex.org/I55240360"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yeong-Seok Seo","raw_affiliation_strings":["Department of Computer Engineering, Yeungnam University, Gyeongsan, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-5319-7674","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Yeungnam University, Gyeongsan, South Korea","institution_ids":["https://openalex.org/I55240360"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119327498","display_name":"Odil Fayzullaev","orcid":null},"institutions":[{"id":"https://openalex.org/I4210143161","display_name":"IDEX Corporation (United States)","ror":"https://ror.org/03jqyh750","country_code":"US","type":"company","lineage":["https://openalex.org/I4210143161"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Odil Fayzullaev","raw_affiliation_strings":["NextPath Innovations LLC., Forest Hills, NY, USA"],"raw_orcid":"https://orcid.org/0009-0000-6094-4781","affiliations":[{"raw_affiliation_string":"NextPath Innovations LLC., Forest Hills, NY, USA","institution_ids":["https://openalex.org/I4210143161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108757915","display_name":"Alexander Azerovich Musaev","orcid":"https://orcid.org/0009-0001-7721-4037"},"institutions":[{"id":"https://openalex.org/I55240360","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159","country_code":"KR","type":"education","lineage":["https://openalex.org/I55240360"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Akobir Musaev","raw_affiliation_strings":["Department of Computer Engineering, Yeungnam University, Gyeongsan, South Korea"],"raw_orcid":"https://orcid.org/0009-0001-7721-4037","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Yeungnam University, Gyeongsan, South Korea","institution_ids":["https://openalex.org/I55240360"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047517734","display_name":"Ngoc Thanh Nguy\u00ean","orcid":"https://orcid.org/0000-0002-3247-2948"},"institutions":[{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Ngoc Thanh Nguyen","raw_affiliation_strings":["Faculty of Information and Communication Technology, Wroc&#x0142;aw University of Science and Technology, Wroc&#x0142;aw, Poland"],"raw_orcid":"https://orcid.org/0000-0002-3247-2948","affiliations":[{"raw_affiliation_string":"Faculty of Information and Communication Technology, Wroc&#x0142;aw University of Science and Technology, Wroc&#x0142;aw, Poland","institution_ids":["https://openalex.org/I686019"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032265881","display_name":"Dosam Hwang","orcid":"https://orcid.org/0000-0001-7851-7323"},"institutions":[{"id":"https://openalex.org/I55240360","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159","country_code":"KR","type":"education","lineage":["https://openalex.org/I55240360"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dosam Hwang","raw_affiliation_strings":["Department of Computer Engineering, Yeungnam University, Gyeongsan, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-7851-7323","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Yeungnam University, Gyeongsan, South Korea","institution_ids":["https://openalex.org/I55240360"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.792,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91415395,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"13","issue":null,"first_page":"138020","last_page":"138036"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9980000257492065,"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/T10862","display_name":"AI in cancer detection","score":0.9980000257492065,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9945999979972839,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"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/dropout","display_name":"Dropout (neural networks)","score":0.7935822010040283},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7281053066253662},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6637454032897949},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6480172872543335},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6101939678192139},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5026166439056396},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48009684681892395},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43990665674209595},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4379946291446686},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33194783329963684}],"concepts":[{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.7935822010040283},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7281053066253662},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6637454032897949},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6480172872543335},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6101939678192139},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5026166439056396},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48009684681892395},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43990665674209595},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4379946291446686},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33194783329963684}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3593046","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3593046","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3118eefb189e4e42849dea5aa419bbf1","is_oa":true,"landing_page_url":"https://doaj.org/article/3118eefb189e4e42849dea5aa419bbf1","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":"IEEE Access, Vol 13, Pp 138020-138036 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3593046","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3593046","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321380","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W768605699","https://openalex.org/W1526606150","https://openalex.org/W1550585437","https://openalex.org/W1806891645","https://openalex.org/W1945616565","https://openalex.org/W2038843977","https://openalex.org/W2087946919","https://openalex.org/W2095705004","https://openalex.org/W2115629999","https://openalex.org/W2146452289","https://openalex.org/W2167917621","https://openalex.org/W2567121296","https://openalex.org/W2618465885","https://openalex.org/W2622999711","https://openalex.org/W2787468747","https://openalex.org/W2794825826","https://openalex.org/W2960665958","https://openalex.org/W2962851944","https://openalex.org/W2963173418","https://openalex.org/W2963946669","https://openalex.org/W2964054038","https://openalex.org/W2964416181","https://openalex.org/W2980444207","https://openalex.org/W2998010746","https://openalex.org/W3034600949","https://openalex.org/W3088070507","https://openalex.org/W3102785203","https://openalex.org/W3109503058","https://openalex.org/W3112953742","https://openalex.org/W3119608944","https://openalex.org/W3122031806","https://openalex.org/W3126968387","https://openalex.org/W3137989655","https://openalex.org/W3203680104","https://openalex.org/W4212883601","https://openalex.org/W4220862496","https://openalex.org/W4226280312","https://openalex.org/W4287660544","https://openalex.org/W4308237781","https://openalex.org/W4312059599","https://openalex.org/W4312612636","https://openalex.org/W4384205849","https://openalex.org/W4385731902","https://openalex.org/W4392811705","https://openalex.org/W4396779912","https://openalex.org/W4398198271","https://openalex.org/W4406278463","https://openalex.org/W6617145748","https://openalex.org/W6631495695","https://openalex.org/W6638667902","https://openalex.org/W6640425456","https://openalex.org/W6674330103","https://openalex.org/W6684191040","https://openalex.org/W6685133223","https://openalex.org/W6749107692","https://openalex.org/W6766394743","https://openalex.org/W6772510107","https://openalex.org/W6792151256"],"related_works":["https://openalex.org/W3082178636","https://openalex.org/W4412335227","https://openalex.org/W2185578297","https://openalex.org/W2782041652","https://openalex.org/W2612657834","https://openalex.org/W2392157706","https://openalex.org/W2599192953","https://openalex.org/W1987310671","https://openalex.org/W2952088488","https://openalex.org/W1521968289"],"abstract_inverted_index":{"To":[0,148],"obtain":[1],"light":[2],"ensemble":[3,9,44,58,63,67,106,146],"model":[4,107,127,131],"through":[5,43],"clearly":[6],"explained":[7],"effective":[8],"member":[10,59],"selection":[11],"and":[12,76,128],"finding":[13],"data":[14,120],"representation":[15],"in":[16,23,41,80,99,114,121],"various":[17,123],"valuable":[18],"forms":[19,85,124],"are":[20],"major":[21],"challenges":[22],"medical":[24,100],"image":[25],"classification":[26,96],"tasks.":[27],"Despite":[28],"numerous":[29],"deep":[30],"learning":[31],"(DL)":[32],"models":[33,49,68],"were":[34],"developed":[35],"to":[36,70,93,111,125,142],"solve":[37],"the":[38,48,51,54,61,87,91,115,119,126,150,153],"generalization":[39],"problem":[40],"DL":[42],"learning,":[45],"most":[46],"of":[47,53,56,74,90,152],"lacks":[50],"evaluation":[52],"effects":[55],"each":[57],"for":[60,159],"final":[62],"model.":[64],"Additionally,":[65],"existing":[66],"tend":[69],"include":[71],"huge":[72],"number":[73],"parameters":[75],"use":[77],"images":[78],"only":[79,144],"RGB":[81],"channels":[82],"or":[83],"greyscale":[84],"missing":[86],"crucial":[88],"representations":[89],"dataset":[92],"reach":[94],"robust":[95],"outcomes,":[97],"particularly":[98],"applications.":[101],"In":[102],"this":[103],"study,":[104],"novel":[105],"IMed-CNN":[108,164],"proposed":[109],"solution":[110],"above-mentioned":[112],"gaps":[113],"field":[116],"by":[117],"introducing":[118],"ten":[122],"applying":[129],"systematic":[130],"dropout":[132],"(SMDE)":[133],"with":[134],"unique":[135],"true":[136],"prediction":[137],"(UTP)":[138],"analysis":[139],"which":[140],"insures":[141],"choose":[143],"useful":[145],"members.":[147],"verify":[149],"performance":[151],"IMed-CNN,":[154],"extensive":[155],"experiments":[156],"was":[157],"designed":[158],"testing.":[160],"Results":[161],"illustrate":[162],"that":[163],"outperformed":[165],"baseline":[166],"models.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}
