{"id":"https://openalex.org/W2779332576","doi":"https://doi.org/10.1109/wincom.2017.8238213","title":"Osteoporosis diagnosis using frequency separation and fractional Brownian motion","display_name":"Osteoporosis diagnosis using frequency separation and fractional Brownian motion","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2779332576","doi":"https://doi.org/10.1109/wincom.2017.8238213","mag":"2779332576"},"language":"en","primary_location":{"id":"doi:10.1109/wincom.2017.8238213","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wincom.2017.8238213","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Wireless Networks and Mobile Communications (WINCOM)","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/A5023564337","display_name":"Abdessamad Tafraouti","orcid":null},"institutions":[{"id":"https://openalex.org/I126477371","display_name":"Mohammed V University","ror":"https://ror.org/00r8w8f84","country_code":"MA","type":"education","lineage":["https://openalex.org/I126477371"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Abdessamad Tafraouti","raw_affiliation_strings":["Faculty of Sciences, University of Mohammed V, Rabat, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Sciences, University of Mohammed V, Rabat, Morocco","institution_ids":["https://openalex.org/I126477371"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046609840","display_name":"Mohammed El Hassouni","orcid":"https://orcid.org/0000-0002-6741-4799"},"institutions":[{"id":"https://openalex.org/I126477371","display_name":"Mohammed V University","ror":"https://ror.org/00r8w8f84","country_code":"MA","type":"education","lineage":["https://openalex.org/I126477371"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Mohammed El Hassouni","raw_affiliation_strings":["Faculty of Sciences, University of Mohammed V, Rabat, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Sciences, University of Mohammed V, Rabat, Morocco","institution_ids":["https://openalex.org/I126477371"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090270022","display_name":"Hechmi Toumi","orcid":"https://orcid.org/0000-0003-4589-7731"},"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"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Hechmi Toumi","raw_affiliation_strings":["Univ. Orl\u00e9ans, I3MTO Laboratory, Orl\u00e9ans, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. Orl\u00e9ans, I3MTO Laboratory, Orl\u00e9ans, 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/I12449238","display_name":"Universit\u00e9 d'Orl\u00e9ans","ror":"https://ror.org/014zrew76","country_code":"FR","type":"education","lineage":["https://openalex.org/I12449238"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Eric Lespessailles","raw_affiliation_strings":["Univ. Orl\u00e9ans, I3MTO Laboratory, Orl\u00e9ans, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. Orl\u00e9ans, I3MTO Laboratory, Orl\u00e9ans, France","institution_ids":["https://openalex.org/I12449238"]}]},{"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"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Rachid Jennane","raw_affiliation_strings":["Univ. Orl\u00e9ans, I3MTO Laboratory, Orl\u00e9ans, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. Orl\u00e9ans, I3MTO Laboratory, Orl\u00e9ans, France","institution_ids":["https://openalex.org/I12449238"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.56,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.95678271,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.9855999946594238,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative 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/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.9855999946594238,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative 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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.945900022983551,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.9341999888420105,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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":0.8119104504585266},{"id":"https://openalex.org/keywords/fractional-brownian-motion","display_name":"Fractional Brownian motion","score":0.5895735025405884},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5592070817947388},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5179999470710754},{"id":"https://openalex.org/keywords/separation","display_name":"Separation (statistics)","score":0.5089309215545654},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4874570369720459},{"id":"https://openalex.org/keywords/brownian-motion","display_name":"Brownian motion","score":0.4814309775829315},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4788079857826233},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37103939056396484},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33116471767425537},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.31951671838760376},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2892777919769287},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19664716720581055},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.1227206289768219}],"concepts":[{"id":"https://openalex.org/C2776541429","wikidata":"https://www.wikidata.org/wiki/Q165328","display_name":"Osteoporosis","level":2,"score":0.8119104504585266},{"id":"https://openalex.org/C108819105","wikidata":"https://www.wikidata.org/wiki/Q1143293","display_name":"Fractional Brownian motion","level":3,"score":0.5895735025405884},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5592070817947388},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5179999470710754},{"id":"https://openalex.org/C2776061190","wikidata":"https://www.wikidata.org/wiki/Q7451805","display_name":"Separation (statistics)","level":2,"score":0.5089309215545654},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4874570369720459},{"id":"https://openalex.org/C112401455","wikidata":"https://www.wikidata.org/wiki/Q178036","display_name":"Brownian motion","level":2,"score":0.4814309775829315},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4788079857826233},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37103939056396484},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33116471767425537},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.31951671838760376},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2892777919769287},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19664716720581055},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.1227206289768219}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wincom.2017.8238213","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wincom.2017.8238213","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Wireless Networks and Mobile Communications (WINCOM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W175660244","https://openalex.org/W1972760573","https://openalex.org/W1978258606","https://openalex.org/W1997927852","https://openalex.org/W2031753087","https://openalex.org/W2032336008","https://openalex.org/W2085803331","https://openalex.org/W2116807840","https://openalex.org/W2118412834","https://openalex.org/W2768149277","https://openalex.org/W4239510810"],"related_works":["https://openalex.org/W2071676784","https://openalex.org/W2373202200","https://openalex.org/W4390048237","https://openalex.org/W1573173092","https://openalex.org/W2753870633","https://openalex.org/W4292513318","https://openalex.org/W3021897514","https://openalex.org/W610640263","https://openalex.org/W4367317527","https://openalex.org/W2960646972"],"abstract_inverted_index":{"Osteoporosis":[0],"is":[1,70],"one":[2],"of":[3,18,23,31,42,52],"the":[4,10,24,29,40,61,73],"most":[5],"common":[6],"bone":[7,57],"diseases":[8],"over":[9],"world,":[11],"this":[12,43,46],"disease":[13],"causes":[14],"a":[15,50],"high":[16],"risk":[17,30],"fracture,":[19],"an":[20,87],"early":[21],"diagnosis":[22,54],"osteoporosis":[25,53],"can":[26],"help":[27],"avoiding":[28],"fracture.":[32],"Several":[33],"methods":[34],"have":[35],"been":[36],"proposed":[37,79],"to":[38],"detect":[39],"presence":[41],"disease.":[44],"In":[45],"paper":[47],"we":[48],"propose":[49],"method":[51,80],"based":[55],"on":[56],"X-Ray":[58],"images,":[59],"using":[60,72],"frequency":[62],"separation":[63],"and":[64],"fractional":[65],"Brownian":[66],"motion.":[67],"The":[68,78],"classification":[69,84],"performed":[71],"Support":[74],"Vector":[75],"Machines":[76],"classifier.":[77],"shows":[81],"its":[82],"good":[83],"performance":[85],"achieving":[86],"accuracy":[88],"rate":[89],"around":[90],"94":[91],"%.":[92]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}