{"id":"https://openalex.org/W2084480234","doi":"https://doi.org/10.1109/ipta.2012.6469528","title":"Osteoporosis assessment using Multilayer Perceptron neural networks","display_name":"Osteoporosis assessment using Multilayer Perceptron neural networks","publication_year":2012,"publication_date":"2012-10-01","ids":{"openalex":"https://openalex.org/W2084480234","doi":"https://doi.org/10.1109/ipta.2012.6469528","mag":"2084480234"},"language":"en","primary_location":{"id":"doi:10.1109/ipta.2012.6469528","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipta.2012.6469528","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005493641","display_name":"Khaled Harrar","orcid":"https://orcid.org/0000-0003-4559-0940"},"institutions":[{"id":"https://openalex.org/I2802493600","display_name":"Polytechnic School of Algiers","ror":"https://ror.org/05t0zwy08","country_code":"DZ","type":"education","lineage":["https://openalex.org/I2802493600"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Khaled Harrar","raw_affiliation_strings":["Signal and communications laboratory, National Polytechnic School, Algiers, Algeria","Signal and communications laboratory, National Polytechnic School, BP 182, 16200 Algiers, Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Signal and communications laboratory, National Polytechnic School, Algiers, Algeria","institution_ids":["https://openalex.org/I2802493600"]},{"raw_affiliation_string":"Signal and communications laboratory, National Polytechnic School, BP 182, 16200 Algiers, Algeria","institution_ids":["https://openalex.org/I2802493600"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079655977","display_name":"Latifa Hamami","orcid":"https://orcid.org/0000-0002-4697-8288"},"institutions":[{"id":"https://openalex.org/I2802493600","display_name":"Polytechnic School of Algiers","ror":"https://ror.org/05t0zwy08","country_code":"DZ","type":"education","lineage":["https://openalex.org/I2802493600"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Latifa Hamami","raw_affiliation_strings":["Signal and communications laboratory, National Polytechnic School, Algiers, Algeria","Signal and communications laboratory, National Polytechnic School, BP 182, 16200 Algiers, Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Signal and communications laboratory, National Polytechnic School, Algiers, Algeria","institution_ids":["https://openalex.org/I2802493600"]},{"raw_affiliation_string":"Signal and communications laboratory, National Polytechnic School, BP 182, 16200 Algiers, Algeria","institution_ids":["https://openalex.org/I2802493600"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072995330","display_name":"Sonia Akkoul","orcid":null},"institutions":[{"id":"https://openalex.org/I12449238","display_name":"Universit\u00e9 d'Orl\u00e9ans","ror":"https://ror.org/014zrew76","country_code":"FR","type":"education","lineage":["https://openalex.org/I12449238"]},{"id":"https://openalex.org/I4210144652","display_name":"Centre hospitalier universitaire d'Orl\u00e9ans","ror":"https://ror.org/04yvax419","country_code":"FR","type":"healthcare","lineage":["https://openalex.org/I4210144652"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Sonia Akkoul","raw_affiliation_strings":["MTO Institute, Hospital of Orleans, Orleans, France","PRISME Laboratory, University of Orleans, 12 rue de Blois BP 6744, 45067 Cedex 2, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MTO Institute, Hospital of Orleans, Orleans, France","institution_ids":["https://openalex.org/I4210144652"]},{"raw_affiliation_string":"PRISME Laboratory, University of Orleans, 12 rue de Blois BP 6744, 45067 Cedex 2, France","institution_ids":["https://openalex.org/I12449238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010199500","display_name":"\u00c9ric Lespessailles","orcid":"https://orcid.org/0000-0003-1009-8518"},"institutions":[{"id":"https://openalex.org/I4210144652","display_name":"Centre hospitalier universitaire d'Orl\u00e9ans","ror":"https://ror.org/04yvax419","country_code":"FR","type":"healthcare","lineage":["https://openalex.org/I4210144652"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Eric Lespessailles","raw_affiliation_strings":["MTO Institute, Hospital of Orleans, Orleans, France","3MTO institute, Hospital of Orleans, 1 rue Porte Madeleine, 45032, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MTO Institute, Hospital of Orleans, Orleans, France","institution_ids":["https://openalex.org/I4210144652"]},{"raw_affiliation_string":"3MTO institute, Hospital of Orleans, 1 rue Porte Madeleine, 45032, France","institution_ids":["https://openalex.org/I4210144652"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037286514","display_name":"Rachid Jennane","orcid":"https://orcid.org/0000-0002-8032-8035"},"institutions":[{"id":"https://openalex.org/I12449238","display_name":"Universit\u00e9 d'Orl\u00e9ans","ror":"https://ror.org/014zrew76","country_code":"FR","type":"education","lineage":["https://openalex.org/I12449238"]},{"id":"https://openalex.org/I4210144652","display_name":"Centre hospitalier universitaire d'Orl\u00e9ans","ror":"https://ror.org/04yvax419","country_code":"FR","type":"healthcare","lineage":["https://openalex.org/I4210144652"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Rachid Jennane","raw_affiliation_strings":["MTO Institute, Hospital of Orleans, Orleans, France","PRISME Laboratory, University of Orleans, 12 rue de Blois BP 6744, 45067 Cedex 2, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MTO Institute, Hospital of Orleans, Orleans, France","institution_ids":["https://openalex.org/I4210144652"]},{"raw_affiliation_string":"PRISME Laboratory, University of Orleans, 12 rue de Blois BP 6744, 45067 Cedex 2, France","institution_ids":["https://openalex.org/I12449238"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.26121795,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"217","last_page":"221"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10071","display_name":"Bone health and osteoporosis research","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/2732","display_name":"Orthopedics and Sports Medicine"},"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/T10071","display_name":"Bone health and osteoporosis research","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/2732","display_name":"Orthopedics and Sports Medicine"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9861000180244446,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11219","display_name":"Bone Metabolism and Diseases","score":0.9686999917030334,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/osteoporosis","display_name":"Osteoporosis","score":0.6426738500595093},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.6395487785339355},{"id":"https://openalex.org/keywords/hurst-exponent","display_name":"Hurst exponent","score":0.6378092765808105},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6271505355834961},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.611093282699585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5795589089393616},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5585978627204895},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5222928524017334},{"id":"https://openalex.org/keywords/cross-validation","display_name":"Cross-validation","score":0.5039798617362976},{"id":"https://openalex.org/keywords/bone-mineral","display_name":"Bone mineral","score":0.4890795350074768},{"id":"https://openalex.org/keywords/fractal","display_name":"Fractal","score":0.4866669774055481},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45731306076049805},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.45441022515296936},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.446550577878952},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.44588813185691833},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34822532534599304},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3462189733982086},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25490903854370117},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2425108551979065},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.17242330312728882},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.06943988800048828}],"concepts":[{"id":"https://openalex.org/C2776541429","wikidata":"https://www.wikidata.org/wiki/Q165328","display_name":"Osteoporosis","level":2,"score":0.6426738500595093},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.6395487785339355},{"id":"https://openalex.org/C96835011","wikidata":"https://www.wikidata.org/wiki/Q1638718","display_name":"Hurst exponent","level":2,"score":0.6378092765808105},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6271505355834961},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.611093282699585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5795589089393616},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5585978627204895},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5222928524017334},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.5039798617362976},{"id":"https://openalex.org/C2776886416","wikidata":"https://www.wikidata.org/wiki/Q4941567","display_name":"Bone mineral","level":3,"score":0.4890795350074768},{"id":"https://openalex.org/C40636538","wikidata":"https://www.wikidata.org/wiki/Q81392","display_name":"Fractal","level":2,"score":0.4866669774055481},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45731306076049805},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.45441022515296936},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.446550577878952},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.44588813185691833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34822532534599304},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3462189733982086},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25490903854370117},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2425108551979065},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.17242330312728882},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.06943988800048828},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ipta.2012.6469528","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipta.2012.6469528","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W58004947","https://openalex.org/W1493459206","https://openalex.org/W1569512666","https://openalex.org/W1970996636","https://openalex.org/W1973933542","https://openalex.org/W2036125852","https://openalex.org/W2069235103","https://openalex.org/W2075361166","https://openalex.org/W2121339236","https://openalex.org/W2130645111","https://openalex.org/W2154918057","https://openalex.org/W2162495444","https://openalex.org/W2165167367","https://openalex.org/W2549349192","https://openalex.org/W2599867508","https://openalex.org/W4285033482","https://openalex.org/W6602323601","https://openalex.org/W6629330598","https://openalex.org/W6839927596"],"related_works":["https://openalex.org/W2368687800","https://openalex.org/W2148767310","https://openalex.org/W2555356437","https://openalex.org/W2417891382","https://openalex.org/W4401177694","https://openalex.org/W2083196709","https://openalex.org/W2600618515","https://openalex.org/W4285523177","https://openalex.org/W1573146092","https://openalex.org/W4396791328"],"abstract_inverted_index":{"The":[0,56],"objective":[1],"of":[2,10,25,31,58,67,70,78,82,102,129,138,140],"this":[3],"paper":[4],"is":[5,61],"to":[6,15,62,73,96,108],"investigate":[7],"the":[8,29,32,59,64,68,75,98,103,123,127,130,141],"effectiveness":[9],"a":[11,23],"Multilayer":[12],"Perceptron":[13],"(MLP)":[14],"discriminate":[16],"subjects":[17],"with":[18],"and":[19,51,85,100,116],"without":[20],"osteoporosis":[21,120],"using":[22],"set":[24],"five":[26,131],"parameters":[27,36],"characterizing":[28],"quality":[30],"bone":[33],"structure.":[34],"These":[35],"include":[37],"Age,":[38],"Bone":[39,43],"mineral":[40,44],"content":[41],"(BMC),":[42],"density":[45],"(BMD),":[46],"fractal":[47],"Hurst":[48],"exponent":[49],"(Hmean)":[50],"coocurrence":[52],"texture":[53],"feature":[54],"(CoEn).":[55],"purpose":[57],"study":[60],"detect":[63],"potential":[65],"usefulness":[66],"combination":[69,128],"different":[71],"features":[72,132],"increase":[74],"classification":[76],"rate":[77],"2":[79],"populations":[80],"composed":[81],"osteporotic":[83],"patients":[84],"control":[86],"subjects.":[87,142],"k-fold":[88],"Cross":[89],"Validation":[90],"(CV)":[91],"was":[92],"used":[93],"in":[94,136],"order":[95],"assess":[97],"accuracy":[99],"reliability":[101],"neural":[104],"network":[105],"validation.":[106],"Compared":[107],"other":[109],"methods":[110],"MLP-based":[111],"analysis":[112],"provides":[113,133],"an":[114],"accurate":[115],"reliable":[117],"platform":[118],"for":[119],"prediction.":[121],"Moreover,":[122],"results":[124],"show":[125],"that":[126],"better":[134],"performance":[135],"terms":[137],"discrimination":[139]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}