{"id":"https://openalex.org/W4416114193","doi":"https://doi.org/10.1109/access.2025.3631513","title":"Automated Diagnosis of Knee Osteoarthritis: A Stacked Ensemble Deep Learning Approach With Explainable AI Techniques","display_name":"Automated Diagnosis of Knee Osteoarthritis: A Stacked Ensemble Deep Learning Approach With Explainable AI Techniques","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416114193","doi":"https://doi.org/10.1109/access.2025.3631513"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3631513","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3631513","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":null,"license_id":null,"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.2025.3631513","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004783243","display_name":"Mohammad Azad","orcid":"https://orcid.org/0000-0001-9851-1420"},"institutions":[{"id":"https://openalex.org/I199702508","display_name":"Jouf University","ror":"https://ror.org/02zsyt821","country_code":"SA","type":"education","lineage":["https://openalex.org/I199702508"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Mohammad Azad","raw_affiliation_strings":["Department of Computer Science, College of Computer and Information Sciences, Jouf University, Sakaka, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0001-9851-1420","affiliations":[{"raw_affiliation_string":"Department of Computer Science, College of Computer and Information Sciences, Jouf University, Sakaka, Saudi Arabia","institution_ids":["https://openalex.org/I199702508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017888285","display_name":"Tanvir Rahman Anik","orcid":null},"institutions":[{"id":"https://openalex.org/I135564639","display_name":"Ahsanullah University of Science and Technology","ror":"https://ror.org/04wfbp123","country_code":"BD","type":"education","lineage":["https://openalex.org/I135564639"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Tanvir Rahman Anik","raw_affiliation_strings":["Department of Computer Science and Engineering, Ahsanullah University of Science and Technology, Dhaka, Bangladesh"],"raw_orcid":"https://orcid.org/0009-0009-2419-5782","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Ahsanullah University of Science and Technology, Dhaka, Bangladesh","institution_ids":["https://openalex.org/I135564639"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.42748345,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"194862","last_page":"194883"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10105","display_name":"Osteoarthritis Treatment and Mechanisms","score":0.6927000284194946,"subfield":{"id":"https://openalex.org/subfields/2745","display_name":"Rheumatology"},"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/T10105","display_name":"Osteoarthritis Treatment and Mechanisms","score":0.6927000284194946,"subfield":{"id":"https://openalex.org/subfields/2745","display_name":"Rheumatology"},"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/T10200","display_name":"Rheumatoid Arthritis Research and Therapies","score":0.031599998474121094,"subfield":{"id":"https://openalex.org/subfields/2745","display_name":"Rheumatology"},"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.01810000091791153,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/deep-learning","display_name":"Deep learning","score":0.6988000273704529},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6420999765396118},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4855000078678131},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4832000136375427},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.4260999858379364},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.41780000925064087},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.39649999141693115},{"id":"https://openalex.org/keywords/osteoarthritis","display_name":"Osteoarthritis","score":0.3953000009059906}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7949000000953674},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7843000292778015},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6988000273704529},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6420999765396118},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5045999884605408},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4855000078678131},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4832000136375427},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4260999858379364},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.41780000925064087},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.39649999141693115},{"id":"https://openalex.org/C2776164576","wikidata":"https://www.wikidata.org/wiki/Q62736","display_name":"Osteoarthritis","level":3,"score":0.3953000009059906},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.375900000333786},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.3481999933719635},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.34549999237060547},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3312999904155731},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.303600013256073},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.2667999863624573},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.25609999895095825},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2538999915122986}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3631513","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3631513","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:81fe7aa5c33e4ced80582956e40f7e12","is_oa":true,"landing_page_url":"https://doaj.org/article/81fe7aa5c33e4ced80582956e40f7e12","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 194862-194883 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3631513","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3631513","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3350607934","display_name":null,"funder_award_id":"DGSSR-2024-02-02103","funder_id":"https://openalex.org/F4320324554","funder_display_name":"Al Jouf University"}],"funders":[{"id":"https://openalex.org/F4320324554","display_name":"Al Jouf University","ror":"https://ror.org/02zsyt821"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1806891645","https://openalex.org/W2108598243","https://openalex.org/W2165698076","https://openalex.org/W2282821441","https://openalex.org/W2616247523","https://openalex.org/W2887031790","https://openalex.org/W3140854437","https://openalex.org/W3171404738","https://openalex.org/W3206366588","https://openalex.org/W4200551431","https://openalex.org/W4210813666","https://openalex.org/W4221119256","https://openalex.org/W4283741762","https://openalex.org/W4293205612","https://openalex.org/W4297973556","https://openalex.org/W4311937545","https://openalex.org/W4318473295","https://openalex.org/W4353100297","https://openalex.org/W4361858356","https://openalex.org/W4362475301","https://openalex.org/W4364381340","https://openalex.org/W4365455479","https://openalex.org/W4367315262","https://openalex.org/W4379880150","https://openalex.org/W4390050126","https://openalex.org/W4392960229","https://openalex.org/W4396972836","https://openalex.org/W4399709922","https://openalex.org/W4400351869","https://openalex.org/W4403451070","https://openalex.org/W4410208049"],"related_works":[],"abstract_inverted_index":{"Knee":[0],"osteoarthritis":[1],"(KOA)":[2],"is":[3,80],"a":[4,55,83,170],"widespread":[5],"degenerative":[6],"joint":[7],"disease":[8],"that":[9,88,173],"poses":[10],"significant":[11],"global":[12],"challenges":[13],"owing":[14],"to":[15,39,180],"delayed":[16],"diagnosis":[17,127],"and":[18,48,66,95,102,117,128,137,152,182],"treatment,":[19],"often":[20],"resulting":[21],"in":[22,125,130],"severe":[23],"disability.":[24],"Despite":[25],"extensive":[26],"research":[27],"on":[28],"predicting":[29],"KOA,":[30],"many":[31],"proposed":[32,109],"methods":[33],"lack":[34],"reliability,":[35],"because":[36],"they":[37],"fail":[38],"incorporate":[40],"explainable":[41],"AI":[42],"(XAI)":[43],"methodologies,":[44],"robust":[45],"preprocessing":[46],"techniques,":[47],"appropriate":[49],"hyperparameter":[50],"tuning.":[51],"This":[52],"study":[53],"introduces":[54],"deep":[56],"learning":[57],"framework":[58],"for":[59,106],"KOA":[60,126,131,185],"classification,":[61],"addressing":[62],"both":[63],"binary":[64],"(diagnosis)":[65],"multi-class":[67],"(severity":[68],"prediction)":[69],"classification":[70],"tasks":[71],"using":[72],"the":[73,163],"Osteoarthritis":[74],"Initiative":[75],"(OAI)":[76],"dataset.":[77],"Our":[78,167],"approach":[79,172],"enhanced":[81],"by":[82],"comprehensive":[84],"image":[85,100],"prepocessing":[86],"pipeline":[87],"includes":[89],"scaling,":[90],"sharpening,":[91],"denoising,":[92],"histogram":[93],"equalization,":[94],"contrast":[96],"enhancement,":[97],"which":[98,113],"standardizes":[99],"quality":[101],"highlights":[103],"crucial":[104],"features":[105],"classification.":[107],"The":[108],"stacked":[110],"ensemble":[111],"model,":[112],"integrates":[114],"Xception,":[115],"EfficientNetB5,":[116],"InceptionV3,":[118],"surpasses":[119],"individual":[120],"models,":[121],"achieving":[122],"86.29%":[123],"accuracy":[124],"96.93%":[129],"severity":[132],"prediction.":[133],"To":[134],"ensure":[135],"transparency":[136],"interpretability,":[138],"we":[139],"incorporated":[140],"advanced":[141],"explainability":[142],"tools,":[143],"including":[144],"Gradient-weighted":[145],"Class":[146],"Activation":[147],"Mapping":[148],"(Grad-CAM),":[149],"Faster":[150],"Score-CAM,":[151],"Local":[153],"Interpretable":[154],"Model-agnostic":[155],"Explanations":[156],"(LIME),":[157],"providing":[158],"clear":[159],"visual":[160],"insights":[161],"into":[162],"model\u2019s":[164],"decision-making":[165],"process.":[166],"findings":[168],"present":[169],"balanced":[171],"combines":[174],"performance":[175],"with":[176],"transparency,":[177],"potentially":[178],"leading":[179],"earlier":[181],"more":[183],"accurate":[184],"diagnoses.":[186]},"counts_by_year":[],"updated_date":"2025-11-28T05:27:51.037384","created_date":"2025-11-11T00:00:00"}
