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VUNO Med-BoneAge

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VUNO Med®-BoneAge™ is an AI-powered diagnostic tool designed to assist healthcare professionals in assessing bone age through the analysis of hand X-ray images. By leveraging deep learning algorithms, it automatically evaluates the X-ray and presents the three most probable bone age candidates, streamlining the diagnostic process and enhancing accuracy. This solution is particularly beneficial in diagnosing growth disorders, such as short stature, tall stature, early or late puberty, and congenital adrenal hyperplasia, by providing precise bone age assessments. Key Features and Functionality: - Automated Bone Age Assessment: Utilizes AI to analyze hand X-ray images, delivering the top three most likely bone age results based on the Greulich-Pyle (GP) method, which categorizes males into 31 groups and females into 27 groups. - Efficient Workflow Integration: Reduces the time required for bone age evaluation by eliminating the need for manual comparison with reference materials. Clinicians can quickly select the most appropriate age from the provided options, enhancing workflow efficiency. - Comprehensive Reporting: Generates detailed reports that include visual graphs projecting the patient's final height, considering factors such as current age, height, and gender. This facilitates clear communication between healthcare providers and patients, improving patient engagement and satisfaction. - Regulatory Approvals: Recognized as Korea's first AI medical device, VUNO Med-BoneAge has received approvals from the Korean Ministry of Food and Drug Safety (MFDS) and the European CE certification, ensuring compliance with international medical standards. Primary Value and User Benefits: VUNO Med-BoneAge addresses the challenges associated with traditional bone age assessment methods, which can be time-consuming and subject to variability among clinicians. By automating the evaluation process, it significantly reduces reading time and enhances the consistency and accuracy of assessments. This leads to more reliable diagnoses of growth-related conditions, enabling timely and appropriate interventions. Additionally, the user-friendly interface and comprehensive reporting support effective communication with patients, fostering better understanding and adherence to treatment plans.

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