{"product_name":"Auto Lung Nodule Detection","company_name":"Samsung","product_url":"https://www.samsung.com","company_url":"https://www.samsung.com","related_urls":["https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-enabled-medical-devices"],"product_code":"SW0382","summary":"Auto Lung Nodule Detection (ALND) is an AI-powered tool developed by Samsung Electronics to assist radiologists in identifying pulmonary nodules in chest X-rays, enhancing diagnostic accuracy and workflow efficiency.","description":"ALND utilizes deep-learning algorithms to detect and highlight suspected lung nodules ranging from 10 to 30mm in size on chest radiographs. Integrated into Samsung's S-Station software, it offers features like automatic detection post-imaging and seamless PACS transmission, aiming to support clinicians in the diagnostic process. The tool has been clinically validated with a sensitivity exceeding 80% in multiple university hospitals, including Freiburg University Hospital, Massachusetts General Hospital, Samsung Medical Center, and Severance Hospital. It received FDA 510(k) clearance in October 2021 and is CE marked for European markets. Samsung has also partnered with Lunit Inc. to further enhance chest abnormality detection capabilities in their digital radiography systems.","categories":["clinical Care","imaging Software","radiology","ai Clinical Documentation Integrity","clinical Decision Support","Clinical","Diagnostic Imaging","Radiology","Artificial Intelligence","Medical Imaging Software"],"market_segment":["Enterprise","SMB"],"target_users":["Radiologists","Clinicians","Medical Imaging Technologists"],"specialties":["Pulmonology","Radiology"],"regions_available":["United States","Europe","South Korea","Germany","Other International Markets"],"languages_supported":["English","Korean","German","Other European Languages"],"pricing_model":"Enterprise_Quote","pricing_details":"Contact vendor for pricing information.","license":"Commercial Proprietary","company_offices":["South Korea","United States","United Kingdom","Germany"],"company_founding":"1969","deployment_model":["on_device","standalone_application","integrated_with_PACS_RIS"],"os_platforms":["Embedded Linux","Windows"],"features":["Automatic detection and marking of suspected pulmonary nodules on chest radiographs","Bounding-box/overlay visualization on images","Designed as a second reader/aid to radiologists","Detects nodules in specified size ranges (10-30 mm)","Real-time/on-device inference during image acquisition","Support for chest AP/PA radiograph views","Integration to display results on acquisition console","Export of annotated images to PACS/DICOM"],"optional_modules":["Autorun for automatic nodule detection post-imaging","PACS transmission options for workflow integration"],"integrations":["Samsung NeuroLogica/Samsung radiography systems (e.g., AccE GC85A, GM85)","PACS (DICOM image export/overlay)","Radiology acquisition console/workstation"],"data_standards":["DICOM","HL7 v2"],"api_available":"unknown","system_requirements":"Runs embedded on supported Samsung digital radiography systems (e.g., GC85A, GM85) and integrates with site PACS/workstation","compliance":["FDA 510(k) cleared","CE (MDD, Class IIa)"],"certifications":["FDA 510(k) clearance (e.g., K201560)","CE (MDD, Class IIa)"],"security_features":["On-device processing for data privacy","Integration with hospital PACS for secure data transmission"],"privacy_features":["Data anonymization during processing","Compliance with healthcare data protection regulations"],"data_residency":"Data processed and stored on-device; integration with hospital PACS allows for data storage within hospital's data residency policies","customers":["Freiburg University Hospital","Massachusetts General Hospital","Samsung Medical Center","Severance Hospital"],"user_reviews":["The Auto Lung Nodule Detection tool has significantly improved our diagnostic accuracy and workflow efficiency.","Integrating ALND into our radiology department has streamlined the process of identifying pulmonary nodules.","The AI-powered detection has reduced the time spent on manual image analysis, allowing us to focus more on patient care.","Since implementing ALND, we've observed a notable increase in early detection rates of lung nodules.","The user-friendly interface of the ALND software has made it easier for our staff to adopt and utilize effectively."],"ratings":["80% sensitivity in clinical evaluations at multiple university hospitals","FDA 510(k) clearance for ALND tool","Recognized by the radiological society for extensive external clinical validation"],"support_channels":["email","phone","chat","ticketing","community","24x7"],"training_options":["documentation","webinars","live_online","onsite","certification"],"release_year":"2021","integration_partners":["Lunit Inc."],"id":"SW0382","slug":"auto-lung-nodule-detection","type":"product","version":"1.0","last_updated":"2025-10-11","links_json":{"self":"https://www.healthaidb.com/software/auto-lung-nodule-detection.json"}}