{"id":"https://openalex.org/W4410927126","doi":"https://doi.org/10.1007/s44230-025-00102-9","title":"Grid Search Based Hyperparameter-Tuned Deep Learning Model for Osteoporosis Diagnosis with Bi-Cubic Interpolation of X-Ray Images","display_name":"Grid Search Based Hyperparameter-Tuned Deep Learning Model for Osteoporosis Diagnosis with Bi-Cubic Interpolation of X-Ray Images","publication_year":2025,"publication_date":"2025-06-01","ids":{"openalex":"https://openalex.org/W4410927126","doi":"https://doi.org/10.1007/s44230-025-00102-9"},"language":"en","primary_location":{"id":"doi:10.1007/s44230-025-00102-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44230-025-00102-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44230-025-00102-9.pdf","source":{"id":"https://openalex.org/S4210207486","display_name":"Human-Centric Intelligent Systems","issn_l":"2667-1336","issn":["2667-1336"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Human-Centric Intelligent Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://link.springer.com/content/pdf/10.1007/s44230-025-00102-9.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100786176","display_name":"Ruhul Amin","orcid":"https://orcid.org/0000-0002-1145-3385"},"institutions":[{"id":"https://openalex.org/I4210148693","display_name":"Metropolitan University","ror":"https://ror.org/04hdrrs71","country_code":"BD","type":"education","lineage":["https://openalex.org/I4210148693"]}],"countries":["BD"],"is_corresponding":true,"raw_author_name":"Ruhul Amin","raw_affiliation_strings":["Department of Computer Science and Engineering, Metropolitan University, Sylhet, 3104, Bangladesh"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Metropolitan University, Sylhet, 3104, Bangladesh","institution_ids":["https://openalex.org/I4210148693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102782097","display_name":"Md. Shamim Reza","orcid":"https://orcid.org/0000-0002-3699-0494"},"institutions":[{"id":"https://openalex.org/I260446899","display_name":"Pabna University of Science and Technology","ror":"https://ror.org/01vxg3438","country_code":"BD","type":"education","lineage":["https://openalex.org/I260446899"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Md.Shamim Reza","raw_affiliation_strings":["Department of Statistics, Pabna University of Science and Technology, Pabna, 6600, Bangladesh"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Pabna University of Science and Technology, Pabna, 6600, Bangladesh","institution_ids":["https://openalex.org/I260446899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059384879","display_name":"Dewan Ahmed Muhtasim","orcid":"https://orcid.org/0000-0002-2513-705X"},"institutions":[{"id":"https://openalex.org/I4210148693","display_name":"Metropolitan University","ror":"https://ror.org/04hdrrs71","country_code":"BD","type":"education","lineage":["https://openalex.org/I4210148693"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Dewan Ahmed Muhtasim","raw_affiliation_strings":["Department of Computer Science and Engineering, Metropolitan University, Sylhet, 3104, Bangladesh"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Metropolitan University, Sylhet, 3104, Bangladesh","institution_ids":["https://openalex.org/I4210148693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005221038","display_name":"Jungpil Shin","orcid":"https://orcid.org/0000-0002-7476-2468"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jungpil Shin","raw_affiliation_strings":["Division of Information Systems, School of Computer Science and Engineering, University of Aizu, Aizu Wakamatsu, Fukushima, 956-8580, Japan"],"affiliations":[{"raw_affiliation_string":"Division of Information Systems, School of Computer Science and Engineering, University of Aizu, Aizu Wakamatsu, Fukushima, 956-8580, Japan","institution_ids":["https://openalex.org/I141591182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017427960","display_name":"Md. Maniruzzaman","orcid":"https://orcid.org/0000-0001-6151-8071"},"institutions":[{"id":"https://openalex.org/I124386471","display_name":"Khulna University","ror":"https://ror.org/05pny7s12","country_code":"BD","type":"education","lineage":["https://openalex.org/I124386471"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Md. Maniruzzaman","raw_affiliation_strings":["Statistics Discipline, Khulna University, Khulna, 9208, Bangladesh"],"affiliations":[{"raw_affiliation_string":"Statistics Discipline, Khulna University, Khulna, 9208, Bangladesh","institution_ids":["https://openalex.org/I124386471"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101347422","display_name":"Md. Mahfujul Hasan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148693","display_name":"Metropolitan University","ror":"https://ror.org/04hdrrs71","country_code":"BD","type":"education","lineage":["https://openalex.org/I4210148693"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Md.Mahfujul Hasan","raw_affiliation_strings":["Department of Computer Science and Engineering, Metropolitan University, Sylhet, 3104, Bangladesh"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Metropolitan University, Sylhet, 3104, Bangladesh","institution_ids":["https://openalex.org/I4210148693"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100786176"],"corresponding_institution_ids":["https://openalex.org/I4210148693"],"apc_list":null,"apc_paid":null,"fwci":0.6627,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.68591248,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"5","issue":"2","first_page":"196","last_page":"208"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.996999979019165,"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/T11363","display_name":"Dental Radiography and Imaging","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/3504","display_name":"Oral Surgery"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.9095420241355896},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"Hyperparameter optimization","score":0.8700230121612549},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.6175898909568787},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.5740781426429749},{"id":"https://openalex.org/keywords/spline-interpolation","display_name":"Spline interpolation","score":0.5023627281188965},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4768023192882538},{"id":"https://openalex.org/keywords/monotone-cubic-interpolation","display_name":"Monotone cubic interpolation","score":0.4747774302959442},{"id":"https://openalex.org/keywords/bicubic-interpolation","display_name":"Bicubic interpolation","score":0.44490790367126465},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4342584013938904},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41221678256988525},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32712483406066895},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31730955839157104},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3120679557323456},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2344660460948944},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.1941365897655487},{"id":"https://openalex.org/keywords/linear-interpolation","display_name":"Linear interpolation","score":0.14285793900489807},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07192161679267883}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.9095420241355896},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.8700230121612549},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.6175898909568787},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.5740781426429749},{"id":"https://openalex.org/C31447003","wikidata":"https://www.wikidata.org/wiki/Q545002","display_name":"Spline interpolation","level":3,"score":0.5023627281188965},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4768023192882538},{"id":"https://openalex.org/C64485984","wikidata":"https://www.wikidata.org/wiki/Q4044484","display_name":"Monotone cubic interpolation","level":5,"score":0.4747774302959442},{"id":"https://openalex.org/C49608258","wikidata":"https://www.wikidata.org/wiki/Q611705","display_name":"Bicubic interpolation","level":4,"score":0.44490790367126465},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4342584013938904},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41221678256988525},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32712483406066895},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31730955839157104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3120679557323456},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2344660460948944},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.1941365897655487},{"id":"https://openalex.org/C171836373","wikidata":"https://www.wikidata.org/wiki/Q2266329","display_name":"Linear interpolation","level":3,"score":0.14285793900489807},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07192161679267883},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44230-025-00102-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44230-025-00102-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44230-025-00102-9.pdf","source":{"id":"https://openalex.org/S4210207486","display_name":"Human-Centric Intelligent Systems","issn_l":"2667-1336","issn":["2667-1336"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Human-Centric Intelligent Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2122e0f35e694be183a6191a46f806c0","is_oa":true,"landing_page_url":"https://doaj.org/article/2122e0f35e694be183a6191a46f806c0","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Human-Centric Intelligent Systems, Vol 5, Iss 2, Pp 196-208 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44230-025-00102-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44230-025-00102-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44230-025-00102-9.pdf","source":{"id":"https://openalex.org/S4210207486","display_name":"Human-Centric Intelligent Systems","issn_l":"2667-1336","issn":["2667-1336"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Human-Centric Intelligent Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410927126.pdf","grobid_xml":"https://content.openalex.org/works/W4410927126.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W2057218377","https://openalex.org/W2062577170","https://openalex.org/W2996161045","https://openalex.org/W3003905048","https://openalex.org/W3027096125","https://openalex.org/W3031675907","https://openalex.org/W3034396835","https://openalex.org/W3034625117","https://openalex.org/W3043664281","https://openalex.org/W3195560828","https://openalex.org/W3195883976","https://openalex.org/W3204648596","https://openalex.org/W4280494417","https://openalex.org/W4293221331","https://openalex.org/W4294608903","https://openalex.org/W4385665444","https://openalex.org/W4386398744","https://openalex.org/W4402489414","https://openalex.org/W4402742550","https://openalex.org/W4403757596","https://openalex.org/W4406085192","https://openalex.org/W4406231895","https://openalex.org/W4406272591","https://openalex.org/W4406371059","https://openalex.org/W6769044626"],"related_works":["https://openalex.org/W2953665647","https://openalex.org/W4281646320","https://openalex.org/W4205712847","https://openalex.org/W3169687406","https://openalex.org/W1974336862","https://openalex.org/W4388119537","https://openalex.org/W2562597462","https://openalex.org/W2009426420","https://openalex.org/W2368242165","https://openalex.org/W2583818965"],"abstract_inverted_index":{"Abstract":[0],"A":[1],"non-communicable":[2],"disease":[3,29],"that":[4],"affects":[5],"the":[6,28,40,52,71,105,139,145,149,159,219,227,240,252,259,263],"bones":[7],"is":[8],"called":[9],"osteoporosis":[10,56,102,192,278],"(OP).":[11],"It":[12],"results":[13,176],"in":[14,249,266],"altered":[15],"bone":[16,19,23],"microstructures,":[17],"insufficient":[18],"regeneration,":[20],"and":[21,47,87,94,99,110,121,170,186,222,229],"decreased":[22],"mineral":[24],"density":[25],"(BMD).":[26],"Until":[27],"progresses,":[30],"individuals":[31],"often":[32],"don't":[33],"realize":[34],"they":[35],"have":[36],"it.":[37],"Even":[38],"with":[39,123,177,215,244],"widespread":[41],"use":[42],"of":[43,55,73,77,262],"deep":[44],"learning":[45,49],"(DL)":[46],"machine":[48],"(ML)":[50],"algorithms,":[51],"early":[53,100],"diagnosis":[54],"patients":[57],"can":[58],"still":[59],"be":[60],"improved.":[61],"By":[62],"automatically":[63],"extracting":[64],"hierarchical":[65],"features":[66,113],"from":[67],"X-ray":[68],"images":[69,147],"through":[70],"application":[72],"a":[74,187,196,246,273],"wide":[75],"range":[76],"competitive":[78],"ML":[79,172],"(Gaussian":[80],"Process":[81],"(GP)":[82],"kernel,":[83],"SVM,":[84],"XGBoost,":[85],"Bagging),":[86],"DL":[88],"models,":[89,173],"we":[90,108,127,143,194],"provide":[91],"highly":[92],"accurate":[93],"consistent":[95],"predictions":[96],"to":[97,137,148,157],"accurately":[98],"predict":[101],"patients.":[103],"In":[104],"proposed":[106,128,163,209],"approach,":[107],"extracted":[109],"integrated":[111],"significant":[112],"using":[114],"three":[115],"image":[116,140,269],"feature":[117],"extractors":[118],"(LBP,":[119],"CLBP,":[120],"HOG)":[122],"95%":[124,223],"PCA.":[125],"Furthermore,":[126],"upscaling":[129],"(2":[130],"\u00d7":[131],"&amp;4":[132],"\u00d7)":[133],"employing":[134],"bicubic":[135],"interpolation":[136],"enhance":[138,191],"intensity.":[141],"Subsequently,":[142],"applied":[144],"interpolated":[146,206],"suggested":[150],"customized":[151],"convolution":[152],"neural":[153],"network":[154],"(CNN)":[155],"model":[156,165,211,265],"improve":[158],"diagnostic":[160],"performance.":[161],"The":[162,208,236],"GP":[164,168,253],"outperformed":[166],"other":[167],"kernel":[169],"traditional":[171],"achieving":[174],"notable":[175],"67.74%":[178],"accuracy,":[179],"61.97%":[180],"precision,":[181],"92.52%":[182],"recall,":[183],"74.12%":[184],"F1-score,":[185],"67.77%":[188],"AUC.":[189],"To":[190],"classification,":[193],"developed":[195],"hybrid":[197],"stacked":[198],"CNN":[199,210,241,264],"model,":[200],"which":[201],"demonstrated":[202],"excellent":[203],"performance":[204],"on":[205,218,225],"images.":[207],"achieved":[212],"state-of-the-art":[213],"results,":[214],"98%":[216],"accuracy":[217,224,250],"training":[220],"set,":[221],"both":[226],"test":[228],"validation":[230],"sets,":[231],"significantly":[232],"surpassing":[233],"existing":[234],"models.":[235],"numerical":[237],"comparison":[238],"shows":[239],"model's":[242],"superiority,":[243],"about":[245],"30%":[247],"increase":[248],"over":[251],"model.":[254],"However,":[255],"this":[256],"research":[257],"demonstrates":[258],"strong":[260],"efficacy":[261],"handling":[267],"complicated":[268],"data,":[270],"making":[271],"it":[272],"more":[274],"sophisticated":[275],"tool":[276],"for":[277],"detection.":[279]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
