{"id":"https://openalex.org/W4415004094","doi":"https://doi.org/10.1109/acit65614.2025.11185886","title":"A Comparative Analysis of YOLOv8, YOLOv9, YOLOv10 and YOLOv11 for Bone Fracture Detection","display_name":"A Comparative Analysis of YOLOv8, YOLOv9, YOLOv10 and YOLOv11 for Bone Fracture Detection","publication_year":2025,"publication_date":"2025-09-17","ids":{"openalex":"https://openalex.org/W4415004094","doi":"https://doi.org/10.1109/acit65614.2025.11185886"},"language":"en","primary_location":{"id":"doi:10.1109/acit65614.2025.11185886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acit65614.2025.11185886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 15th International Conference on Advanced Computer Information Technologies (ACIT)","raw_type":"proceedings-article"},"type":"article","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/A5119925194","display_name":"Nisanur Pirin\u00e7ci","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Nisanur Pirin\u00e7ci","raw_affiliation_strings":["Fırat University,Department of Computer Engineering,Elazığ,Turkey"],"affiliations":[{"raw_affiliation_string":"Fırat University,Department of Computer Engineering,Elazığ,Turkey","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"\u0130brahim Ethem \u00d6zdemir","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"\u0130brahim Ethem \u00d6zdemir","raw_affiliation_strings":["Fırat University,Department of Computer Engineering,Elazığ,Turkey"],"affiliations":[{"raw_affiliation_string":"Fırat University,Department of Computer Engineering,Elazığ,Turkey","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5119925195","display_name":"Ertan B\u00fct\u00fcn","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ertan B\u00fct\u00fcn","raw_affiliation_strings":["Fırat University,Department of Computer Engineering,Elazığ,Turkey"],"affiliations":[{"raw_affiliation_string":"Fırat University,Department of Computer Engineering,Elazığ,Turkey","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5119925194"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.40671476,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"884","last_page":"887"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9713000059127808,"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"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9713000059127808,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.6381000280380249},{"id":"https://openalex.org/keywords/fracture","display_name":"Fracture (geology)","score":0.545799970626831},{"id":"https://openalex.org/keywords/diagnostic-accuracy","display_name":"Diagnostic accuracy","score":0.4187000095844269},{"id":"https://openalex.org/keywords/bone-fracture","display_name":"Bone fracture","score":0.3862999975681305},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.37130001187324524},{"id":"https://openalex.org/keywords/clinical-practice","display_name":"Clinical Practice","score":0.3366999924182892}],"concepts":[{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6381000280380249},{"id":"https://openalex.org/C43369102","wikidata":"https://www.wikidata.org/wiki/Q2307625","display_name":"Fracture (geology)","level":2,"score":0.545799970626831},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4237000048160553},{"id":"https://openalex.org/C3020132585","wikidata":"https://www.wikidata.org/wiki/Q2671652","display_name":"Diagnostic accuracy","level":2,"score":0.4187000095844269},{"id":"https://openalex.org/C2776441800","wikidata":"https://www.wikidata.org/wiki/Q68833","display_name":"Bone fracture","level":2,"score":0.3862999975681305},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37380000948905945},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.37130001187324524},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.36910000443458557},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C29694066","wikidata":"https://www.wikidata.org/wiki/Q118301","display_name":"Orthodontics","level":1,"score":0.2928999960422516},{"id":"https://openalex.org/C3020175042","wikidata":"https://www.wikidata.org/wiki/Q2145130","display_name":"Fracture reduction","level":3,"score":0.28459998965263367},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C40993552","wikidata":"https://www.wikidata.org/wiki/Q514654","display_name":"Gold standard (test)","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acit65614.2025.11185886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acit65614.2025.11185886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 15th International Conference on Advanced Computer Information Technologies (ACIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2949736877","https://openalex.org/W3106753828","https://openalex.org/W4210598935","https://openalex.org/W4381891769","https://openalex.org/W4385616367","https://openalex.org/W4388200034","https://openalex.org/W4390638513","https://openalex.org/W4391589177","https://openalex.org/W4400411497","https://openalex.org/W4402613813","https://openalex.org/W4403653357","https://openalex.org/W4403770406","https://openalex.org/W4409709759"],"related_works":[],"abstract_inverted_index":{"Early":[0],"diagnosis":[1,129],"of":[2,25,56,62,75,100,103,107,111,117],"bone":[3,46],"fractures":[4,47],"is":[5],"critical":[6],"for":[7],"treatment":[8],"success,":[9],"and":[10,14,43,73,105,126],"collaboration":[11],"between":[12],"radiologists":[13],"surgeons":[15],"plays":[16],"a":[17,98],"crucial":[18],"role":[19],"in":[20,33,48],"this":[21,112],"process.":[22],"The":[23,60,109],"use":[24],"advanced":[26],"technologies":[27],"accelerates":[28],"the":[29,49,53,57,71,79,82,88,115],"diagnostic":[30],"process,":[31],"resulting":[32],"improved":[34],"patient":[35],"health":[36],"outcomes.":[37],"This":[38],"study":[39,80,113],"aims":[40],"to":[41,122],"accurately":[42],"effectively":[44],"detect":[45],"FracAtlas":[50],"dataset":[51],"using":[52],"latest":[54],"variants":[55],"YOLO":[58],"architecture.":[59],"integration":[61],"deep":[63],"learning":[64],"architectures":[65],"with":[66,92],"data":[67,94],"augmentation":[68,95],"techniques":[69],"improves":[70],"accuracy":[72],"reliability":[74],"fracture":[76,119,128],"detection.":[77],"In":[78],"results,":[81],"best":[83],"performance":[84],"was":[85],"achieved":[86],"by":[87],"YOLOv10x":[89],"model":[90],"combined":[91],"automatic":[93],"techniques,":[96],"yielding":[97],"precision":[99],"0.882,":[101],"recall":[102],"0.758":[104],"mAP@50":[106],"0.8016.":[108],"findings":[110],"underscore":[114],"potential":[116],"AI-powered":[118],"detection":[120],"systems":[121],"improve":[123],"clinical":[124],"decisions":[125],"expedite":[127],"delays.":[130]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}