{"id":"https://openalex.org/W4412467403","doi":"https://doi.org/10.1007/s11063-025-11782-6","title":"MSFKAN: A Multi-Scale Feature Prediction Network Combined with KAN for Medical Image Classification","display_name":"MSFKAN: A Multi-Scale Feature Prediction Network Combined with KAN for Medical Image Classification","publication_year":2025,"publication_date":"2025-07-16","ids":{"openalex":"https://openalex.org/W4412467403","doi":"https://doi.org/10.1007/s11063-025-11782-6"},"language":"en","primary_location":{"id":"doi:10.1007/s11063-025-11782-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11782-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-025-11782-6.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"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-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11063-025-11782-6.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010203151","display_name":"Jianyun Gao","orcid":"https://orcid.org/0009-0009-0656-3123"},"institutions":[{"id":"https://openalex.org/I4210136676","display_name":"National Institutes for Food and Drug Control","ror":"https://ror.org/041rdq190","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210136676"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianyun Gao","raw_affiliation_strings":["Institute for Medical Device Control, National Institutes for Food and Drug Control, Beijing, 102629, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute for Medical Device Control, National Institutes for Food and Drug Control, Beijing, 102629, Beijing, China","institution_ids":["https://openalex.org/I4210136676"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100607217","display_name":"Yuan Liao","orcid":"https://orcid.org/0000-0001-8268-6947"},"institutions":[{"id":"https://openalex.org/I4210150693","display_name":"The Medical Device (United Kingdom)","ror":"https://ror.org/059mrwr24","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210150693"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yuan Liao","raw_affiliation_strings":["Active medical device testing department, Yunnan Institute of Medical Device Testing, Kunming, 650106, Yunnan, China"],"affiliations":[{"raw_affiliation_string":"Active medical device testing department, Yunnan Institute of Medical Device Testing, Kunming, 650106, Yunnan, China","institution_ids":["https://openalex.org/I4210150693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102016292","display_name":"Zerui Zhang","orcid":"https://orcid.org/0000-0002-5401-0621"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zerui Zhang","raw_affiliation_strings":["School of Bioengineering, Chongqing University, Chongqing, 400044, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Bioengineering, Chongqing University, Chongqing, 400044, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100404334","display_name":"Shu Li","orcid":"https://orcid.org/0000-0003-1742-2480"},"institutions":[{"id":"https://openalex.org/I4210136676","display_name":"National Institutes for Food and Drug Control","ror":"https://ror.org/041rdq190","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210136676"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shu Li","raw_affiliation_strings":["Institute for Medical Device Control, National Institutes for Food and Drug Control, Beijing, 102629, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute for Medical Device Control, National Institutes for Food and Drug Control, Beijing, 102629, Beijing, China","institution_ids":["https://openalex.org/I4210136676"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100446223","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0003-4563-1132"},"institutions":[{"id":"https://openalex.org/I4210136676","display_name":"National Institutes for Food and Drug Control","ror":"https://ror.org/041rdq190","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210136676"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wang","raw_affiliation_strings":["Institute for Medical Device Control, National Institutes for Food and Drug Control, Beijing, 102629, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute for Medical Device Control, National Institutes for Food and Drug Control, Beijing, 102629, Beijing, China","institution_ids":["https://openalex.org/I4210136676"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5010203151"],"corresponding_institution_ids":["https://openalex.org/I4210136676"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":15.3079,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.98743589,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"57","issue":"4","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9994000196456909,"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":0.9994000196456909,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9979000091552734,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computational-intelligence","display_name":"Computational intelligence","score":0.7629909515380859},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6238852143287659},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6024873852729797},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5896003246307373},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5289989113807678},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5239622592926025},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4785062372684479},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.08934196829795837},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07648119330406189},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.06480956077575684}],"concepts":[{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.7629909515380859},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6238852143287659},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6024873852729797},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5896003246307373},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5289989113807678},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5239622592926025},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4785062372684479},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.08934196829795837},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07648119330406189},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.06480956077575684},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11063-025-11782-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11782-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-025-11782-6.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"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-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11063-025-11782-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11782-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-025-11782-6.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"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-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320317237","display_name":"National Institutes for Food and Drug Control","ror":"https://ror.org/041rdq190"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412467403.pdf","grobid_xml":"https://content.openalex.org/works/W4412467403.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W2040600853","https://openalex.org/W2100495367","https://openalex.org/W2183159415","https://openalex.org/W2301401860","https://openalex.org/W2420085356","https://openalex.org/W2520016695","https://openalex.org/W2533800772","https://openalex.org/W2592929672","https://openalex.org/W2919115771","https://openalex.org/W2963946669","https://openalex.org/W3011430986","https://openalex.org/W3015058572","https://openalex.org/W3017451406","https://openalex.org/W3034429256","https://openalex.org/W3129469040","https://openalex.org/W3157726815","https://openalex.org/W4224932948","https://openalex.org/W4240429504","https://openalex.org/W4255289481","https://openalex.org/W4312443924","https://openalex.org/W4313554895","https://openalex.org/W4361007602","https://openalex.org/W4379534745","https://openalex.org/W4391253217","https://openalex.org/W4392397365","https://openalex.org/W4392607494","https://openalex.org/W4396973073","https://openalex.org/W4405760644","https://openalex.org/W6600302053","https://openalex.org/W6600351811","https://openalex.org/W6602783575","https://openalex.org/W6687483927"],"related_works":["https://openalex.org/W2736674626","https://openalex.org/W2973875853","https://openalex.org/W3147584709","https://openalex.org/W2977677679","https://openalex.org/W1992327129","https://openalex.org/W2381986121","https://openalex.org/W2370918718","https://openalex.org/W1987895166","https://openalex.org/W2256933480","https://openalex.org/W2027854990"],"abstract_inverted_index":{"The":[0,118],"characteristics":[1],"of":[2,23,35,87,166,195,206,218,241,262],"the":[3,21,31,67,102,112,133,151,175,183,192,196,211,215,219,232,239,260],"lesion":[4],"areas":[5],"in":[6,111,157,250],"medical":[7,36,58,129,252,263],"images":[8],"are":[9,81,93],"complex,":[10],"and":[11,101,106,123,142,180,208,222,248],"existing":[12],"fully":[13],"connected":[14],"layer-based":[15],"neural":[16],"networks":[17],"still":[18],"cannot":[19],"address":[20],"issue":[22],"linear":[24],"kernels,":[25],"making":[26],"them":[27],"inadequate":[28],"for":[29,57,116,168,174,182],"handling":[30],"nonlinear":[32],"classification":[33,60,158,193],"problem":[34],"image":[37,59,130,136],"data.":[38],"This":[39,189,254],"paper":[40],"investigates":[41],"a":[42,53,97,203],"multi-scale":[43],"feature":[44,85,91],"joint":[45],"prediction":[46,70],"Kolmogorov-Arnold":[47,74,113],"Network":[48,114],"convolutional":[49,79],"network":[50,71],"combined":[51,72],"with":[52,73],"spatial":[54,98],"attention":[55,99],"mechanism":[56],"applications.":[61],"In":[62,76],"this":[63,77],"article,":[64],"we":[65,201],"propose":[66],"Multi-Scale":[68],"Feature":[69],"Network.":[75],"model,":[78],"blocks":[80],"concatenated":[82],"to":[83,258],"output":[84,103],"maps":[86,92],"different":[88,251],"scales.":[89],"These":[90],"then":[94],"passed":[95],"through":[96],"module,":[100],"is":[104,120,256],"weighted":[105],"summed":[107],"using":[108,210],"learnable":[109],"weights":[110],"layer":[115],"classification.":[117,188,265],"model":[119,153],"trained,":[121],"tuned,":[122],"tested":[124],"on":[125,214],"three":[126,220],"publicly":[127],"available":[128],"datasets,":[131,162],"including":[132],"skin":[134,170],"cancer":[135,171],"dataset,":[137,141],"COVID-19":[138,177],"lung":[139],"CT":[140,178,187],"brain":[143,185],"tumor":[144,186],"MRI":[145],"dataset.":[146],"Experimental":[147],"results":[148,237],"show":[149],"that":[150,225],"proposed":[152,243],"demonstrates":[154],"strong":[155],"performance":[156,190,261],"tasks":[159],"across":[160],"four":[161],"achieving":[163],"an":[164],"accuracy":[165,194,230],"87.27%":[167],"binary":[169],"classification,":[172,179],"94.12%":[173],"three-class":[176],"97.48%":[181],"four-class":[184],"outperforms":[191],"selected":[197],"comparison":[198,233],"methods.":[199,234],"Additionally,":[200],"applied":[202],"perturbation":[204],"rate":[205],"0.5%":[207],"1.0%":[209],"FGSM":[212],"method":[213,227],"test":[216],"sets":[217],"datasets":[221],"re-tested,":[223],"finding":[224],"our":[226,242],"achieved":[228],"higher":[229],"than":[231],"Comprehensive":[235],"experimental":[236],"validate":[238],"effectiveness":[240],"method,":[244],"demonstrating":[245],"its":[246],"applicability":[247],"robustness":[249],"scenarios.":[253],"approach":[255],"expected":[257],"enhance":[259],"image-assisted":[264]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-10T00:00:00"}