{"product_name":"RBknee","company_name":"Radiobotics","product_url":"https://radiobotics.com/products/rbknee","company_url":"https://radiobotics.com","related_urls":["https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-enabled-medical-devices"],"product_code":"SW0453","summary":"RBknee is an AI-powered software developed by Radiobotics that automates the analysis of knee X-rays to assist in diagnosing knee osteoarthritis, providing objective measurements and standardized grading to support medical professionals in evaluation and treatment planning.","description":"RBknee utilizes machine learning algorithms to analyze digital knee X-rays, identifying radiographic signs associated with osteoarthritis, such as joint space narrowing, osteophytes, and subchondral sclerosis. It measures joint space width in both knee compartments and provides standardized grading based on Kellgren-Lawrence criteria, aiding clinicians in accurate diagnosis and treatment decisions.","categories":["diagnostic Support","clinical Care","radiology","Diagnostic","Clinical","Radiology","Musculoskeletal"],"market_segment":["enterprise","smb"],"target_users":["clinicians","radiologists","orthopedic surgeons"],"specialties":["Orthopedics","Radiology","Musculoskeletal Disorders"],"regions_available":["United States","European Union"],"languages_supported":["English","Danish"],"pricing_model":"subscription","pricing_details":"Contact vendor for pricing information.","license":"commercial","company_offices":["Denmark","United States"],"company_founding":"2017","deployment_model":["SaaS","on_prem","hybrid"],"os_platforms":["Web","iOS","Android","Windows","macOS","Linux"],"features":["Automated detection of knee osteoarthritis (OA) on X-rays","Identification of osteophytes, subchondral sclerosis, and joint space narrowing","Generation of OA grading reports based on the Kellgren-Lawrence scale","Integration with standard reading environments (PACS)","Integration with Radiological Information Systems (RIS)","Integration via AI marketplaces or distribution platforms","Deployment options: locally virtualized (virtual machine, Docker) or cloud-based","Analysis triggered automatically post-image acquisition or on-demand by user","Processing time: less than 3 seconds per image","Secondary capture with annotated regions of interest highlighting OA signs","CE-marked as Class IIa medical device under MDR","FDA 510(k) cleared as Class II medical device","Intended for use as an adjunctive tool to assist healthcare professionals in radiographic analysis and reporting on knee OA from lateral and weight-bearing anterior-posterior or posterior-anterior projection radiographs of unilateral or bilateral knees"],"optional_modules":[],"integrations":["PACS","RIS","AI marketplaces","distribution platforms"],"data_standards":["DICOM"],"api_available":"unknown","system_requirements":"Major OS/DB/hardware needs, or empty if SaaS-only","compliance":["HIPAA","GDPR","HITECH","SOC 2","ISO 27001"],"certifications":["FDA 510(k)","CE/MDR","ISO 13485"],"security_features":["Encryption","RBAC","SSO/SAML","audit logs","2FA","DLP"],"privacy_features":["BAA available","consent mgmt","anonymization","data minimization"],"data_residency":"US/EU regions","customers":["Kettering General Hospital Foundation Trust"],"user_reviews":["I never thought AI solutions for fracture detection would be useful for an experienced reporter, but RBfracture caught several fractures that I would have otherwise missed."],"ratings":["94% accuracy, specificity, and sensitivity","86% reduction in missed fracture rate","13s median processing time per exam"],"support_channels":["email","phone","chat","ticketing","community","24x7"],"training_options":["documentation","webinars","live_online","onsite","certification"],"release_year":"2024","integration_partners":["Aarhus University Hospital"],"id":"SW0453","slug":"rbknee","type":"product","version":"1.0","last_updated":"2025-10-11","links_json":{"self":"https://www.healthaidb.com/software/rbknee.json"}}