{"id":"https://openalex.org/W7125929416","doi":"https://doi.org/10.1155/acis/7826423","title":"Automated Diagnosis of Lower Limb Alignment Deformities Using Deep Learning and Joint Orientation Analysis","display_name":"Automated Diagnosis of Lower Limb Alignment Deformities Using Deep Learning and Joint Orientation Analysis","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7125929416","doi":"https://doi.org/10.1155/acis/7826423"},"language":"en","primary_location":{"id":"doi:10.1155/acis/7826423","is_oa":true,"landing_page_url":"https://doi.org/10.1155/acis/7826423","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1155/acis/7826423","source":{"id":"https://openalex.org/S30680879","display_name":"Applied Computational Intelligence and Soft Computing","issn_l":"1687-9724","issn":["1687-9724","1687-9732"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Computational Intelligence and Soft Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1155/acis/7826423","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076466484","display_name":"Aarti Goswami","orcid":null},"institutions":[{"id":"https://openalex.org/I73779912","display_name":"Manipal University Jaipur","ror":"https://ror.org/040h76494","country_code":null,"type":"education","lineage":["https://openalex.org/I73779912"]}],"countries":[],"is_corresponding":true,"raw_author_name":"Aarti Goswami","raw_affiliation_strings":["Department of Computer Science Application ,  School of Computer Science & Engineering ,  Manipal University Jaipur ,  Jaipur , Rajasthan,  India ,  manipal.edu"],"raw_orcid":"https://orcid.org/0009-0003-3066-8562","affiliations":[{"raw_affiliation_string":"Department of Computer Science Application ,  School of Computer Science & Engineering ,  Manipal University Jaipur ,  Jaipur , Rajasthan,  India ,  manipal.edu","institution_ids":["https://openalex.org/I73779912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124107191","display_name":"Sandeep Chaurasia","orcid":null},"institutions":[{"id":"https://openalex.org/I73779912","display_name":"Manipal University Jaipur","ror":"https://ror.org/040h76494","country_code":null,"type":"education","lineage":["https://openalex.org/I73779912"]}],"countries":[],"is_corresponding":true,"raw_author_name":"Sandeep Chaurasia","raw_affiliation_strings":["Department of Computer Science & Engineering ,  School of Computer Science & Engineering ,  Manipal University Jaipur ,  Jaipur , Rajasthan,  India ,  manipal.edu"],"raw_orcid":"https://orcid.org/0000-0002-0935-9795","affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering ,  School of Computer Science & Engineering ,  Manipal University Jaipur ,  Jaipur , Rajasthan,  India ,  manipal.edu","institution_ids":["https://openalex.org/I73779912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037288172","display_name":"Jayesh Gangrade","orcid":"https://orcid.org/0000-0001-9593-5308"},"institutions":[{"id":"https://openalex.org/I73779912","display_name":"Manipal University Jaipur","ror":"https://ror.org/040h76494","country_code":null,"type":"education","lineage":["https://openalex.org/I73779912"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Jayesh Gangrade","raw_affiliation_strings":["Department of Artificial Intelligence & Machine Learning ,  School of Computer Science & Engineering ,  Manipal University Jaipur ,  Jaipur , Rajasthan,  India ,  manipal.edu"],"raw_orcid":"https://orcid.org/0000-0001-9593-5308","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence & Machine Learning ,  School of Computer Science & Engineering ,  Manipal University Jaipur ,  Jaipur , Rajasthan,  India ,  manipal.edu","institution_ids":["https://openalex.org/I73779912"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124121691","display_name":"Gopalakrishnan T.","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Gopalakrishnan T.","raw_affiliation_strings":["Manipal Institute of Technology Bengaluru ,  Manipal Academy of Higher Education ,  Manipal ,  India ,  manipal.edu"],"raw_orcid":"https://orcid.org/0000-0002-3124-322X","affiliations":[{"raw_affiliation_string":"Manipal Institute of Technology Bengaluru ,  Manipal Academy of Higher Education ,  Manipal ,  India ,  manipal.edu","institution_ids":["https://openalex.org/I164861460"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5076466484","https://openalex.org/A5124107191","https://openalex.org/A5124121691"],"corresponding_institution_ids":["https://openalex.org/I164861460","https://openalex.org/I73779912"],"apc_list":{"value":900,"currency":"USD","value_usd":900},"apc_paid":{"value":900,"currency":"USD","value_usd":900},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14946104,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2026","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10105","display_name":"Osteoarthritis Treatment and Mechanisms","score":0.15719999372959137,"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":0.15719999372959137,"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/T10562","display_name":"Total Knee Arthroplasty Outcomes","score":0.15620000660419464,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/T10442","display_name":"Knee injuries and reconstruction techniques","score":0.13519999384880066,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/false-positive-paradox","display_name":"False positive paradox","score":0.695900022983551},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5999000072479248},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5630999803543091},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5612999796867371},{"id":"https://openalex.org/keywords/confusion-matrix","display_name":"Confusion matrix","score":0.5230000019073486},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5049999952316284},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.4878000020980835},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45019999146461487},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.35249999165534973}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8205000162124634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7573999762535095},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.695900022983551},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5999000072479248},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5630999803543091},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5612999796867371},{"id":"https://openalex.org/C138602881","wikidata":"https://www.wikidata.org/wiki/Q2709591","display_name":"Confusion matrix","level":2,"score":0.5230000019073486},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5049999952316284},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.4878000020980835},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45019999146461487},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39469999074935913},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.35249999165534973},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35109999775886536},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.350600004196167},{"id":"https://openalex.org/C2778640784","wikidata":"https://www.wikidata.org/wiki/Q168002","display_name":"Ankle","level":2,"score":0.34439998865127563},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.3425000011920929},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.31049999594688416},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C2986587452","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical analysis","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.26010000705718994},{"id":"https://openalex.org/C112789634","wikidata":"https://www.wikidata.org/wiki/Q18207010","display_name":"False positives and false negatives","level":3,"score":0.2533000111579895}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/acis/7826423","is_oa":true,"landing_page_url":"https://doi.org/10.1155/acis/7826423","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1155/acis/7826423","source":{"id":"https://openalex.org/S30680879","display_name":"Applied Computational Intelligence and Soft Computing","issn_l":"1687-9724","issn":["1687-9724","1687-9732"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Computational Intelligence and Soft Computing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:78236a2222314361aacd662b4ceb722f","is_oa":true,"landing_page_url":"https://doaj.org/article/78236a2222314361aacd662b4ceb722f","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":"Applied Computational Intelligence and Soft Computing, Vol 2026 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/acis/7826423","is_oa":true,"landing_page_url":"https://doi.org/10.1155/acis/7826423","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1155/acis/7826423","source":{"id":"https://openalex.org/S30680879","display_name":"Applied Computational Intelligence and Soft Computing","issn_l":"1687-9724","issn":["1687-9724","1687-9732"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Computational Intelligence and Soft Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7125929416.pdf","grobid_xml":"https://content.openalex.org/works/W7125929416.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W129290829","https://openalex.org/W1999114171","https://openalex.org/W1999126347","https://openalex.org/W2000275839","https://openalex.org/W2043659370","https://openalex.org/W2156430261","https://openalex.org/W2257322956","https://openalex.org/W2545698454","https://openalex.org/W2713510692","https://openalex.org/W2914285814","https://openalex.org/W2951269226","https://openalex.org/W2971226805","https://openalex.org/W2999309192","https://openalex.org/W3014606606","https://openalex.org/W3046828652","https://openalex.org/W3048149209","https://openalex.org/W3049181706","https://openalex.org/W3052072725","https://openalex.org/W3094608477","https://openalex.org/W3102927640","https://openalex.org/W3122532105","https://openalex.org/W3168789724","https://openalex.org/W3183382886","https://openalex.org/W3196310256","https://openalex.org/W4214873977","https://openalex.org/W4308197876","https://openalex.org/W4309874705","https://openalex.org/W4324149877","https://openalex.org/W4360971374","https://openalex.org/W4367294659","https://openalex.org/W4386608427","https://openalex.org/W4388490814","https://openalex.org/W4388495294","https://openalex.org/W4390204081","https://openalex.org/W4401081598","https://openalex.org/W4409180296","https://openalex.org/W4412934661"],"related_works":[],"abstract_inverted_index":{"The":[0,57,114,206],"misalignment":[1,235],"of":[2,22,50,125,128,131,134,139,240,253,260,266,272,277,286,297],"the":[3,15,19,48,85,89,94,101,119,146,229,248,254,295,298],"lower":[4,51],"limbs":[5],"may":[6],"cause":[7],"serious":[8],"musculoskeletal":[9],"issues":[10],"when":[11],"not":[12],"discovered":[13],"at":[14],"initial":[16],"stage,":[17],"but":[18],"traditional":[20,147],"methods":[21,104],"diagnosis":[23],"are":[24],"subjective,":[25],"time\u2010consuming,":[26],"and":[27,71,97,100,108,136,160,200,222,250,281,304],"rely":[28],"on":[29],"clinical":[30,312],"experience.":[31],"In":[32],"solving":[33],"these":[34,83,168],"problems,":[35],"this":[36],"paper":[37],"will":[38],"present":[39],"an":[40,137],"automated":[41],"convolutional":[42],"neural":[43],"network":[44],"(CNN)":[45],"to":[46,63,110],"identify":[47],"presence":[49],"limb":[52],"misalignments":[53],"in":[54,232,300],"X\u2010ray":[55],"images.":[56,243],"anatomical":[58],"landmarks":[59],"have":[60,76],"been":[61,69],"identified":[62],"be":[64],"complex,":[65],"image":[66],"quality":[67],"has":[68],"inconsistent,":[70],"limited":[72],"datasets":[73],"with":[74,173,213],"labels":[75],"historically":[77],"obstructed":[78],"consistent":[79],"diagnosis.":[80],"To":[81],"overcome":[82],"difficulties,":[84],"proposed":[86],"CNN":[87,120],"recognizes":[88],"most":[90],"important":[91],"landmarks,":[92],"i.e.,":[93],"hip,":[95],"knee,":[96],"ankle":[98],"joints,":[99],"data":[102],"augmentation":[103],"made":[105],"it":[106,307],"stronger":[107],"flexible":[109],"various":[111],"imaging":[112],"characteristics.":[113],"comparative":[115],"analysis":[116,166,209],"showed":[117],"that":[118],"had":[121],"a":[122,257,308],"high":[123,283],"accuracy":[124,259],"94.11,":[126],"precision":[127,265],"1.00,":[129],"recall":[130,271],"0.91666,":[132],"F1\u2010score":[133,276],"0.9565,":[135],"AUC":[138,284],"0.97,":[140],"which":[141],"is":[142],"significantly":[143],"better":[144],"than":[145],"models":[148],"such":[149],"as":[150],"support":[151],"vector":[152],"machine":[153],"(SVM),":[154],"random":[155],"forest":[156],"(RF),":[157],"logistic":[158,198],"regression,":[159,199],"fully":[161],"connected":[162],"networks":[163],"(FCNs).":[164],"Statistical":[165],"confirmed":[167,247],"performance":[169,212],"differences":[170],"were":[171],"significant,":[172],"paired":[174],"t":[175],"\u2010tests":[176],"showing":[177],"p":[178,184,189,194,201],"values":[179,285],"well":[180],"below":[181],"0.05":[182],"(":[183],"=":[185,195,202],"0.004932":[186],"for":[187,192,197,204,311],"SVM,":[188],"<":[190],"0.000001":[191],"RF,":[193],"0.000197":[196],"0.000031":[203],"FCN).":[205],"confusion":[207],"matrix":[208],"revealed":[210],"exceptional":[211],"44":[214],"true":[215],"positives":[216,220],"(TP),":[217],"0":[218],"false":[219,225],"(FP),":[221],"only":[223],"4":[224],"negatives":[226],"(FN),":[227],"demonstrating":[228],"model\u2019s":[230],"proficiency":[231],"accurately":[233],"identifying":[234],"cases":[236],"while":[237],"preventing":[238],"misclassification":[239],"properly":[241],"aligned":[242],"Furthermore,":[244],"10\u2010fold":[245],"cross\u2010validation":[246],"stability":[249],"generalization":[251],"capacity":[252],"CNN,":[255],"yielding":[256],"mean":[258],"93.98%":[261],"\u00b1":[262,268,274,279,288],"0.0124,":[263],"flawless":[264],"1.00":[267],"0.00,":[269],"strong":[270],"0.9168":[273],"0.0201,":[275],"0.9565":[278],"0.0128,":[280],"consistently":[282],"0.9662":[287],"0.0107":[289],"across":[290],"folds.":[291],"These":[292],"outcomes":[293],"emphasize":[294],"reliability":[296],"model":[299],"minimizing":[301],"both":[302],"FP":[303],"FN,":[305],"making":[306],"dependable":[309],"tool":[310],"applications.":[313]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2026-01-29T00:00:00"}