Medical artificial intelligence (AI) solutions developer VUNO, in partnership with a member of the Born2Global Centre, has secured the Class 2a CE marking approval for five AI solutions.
The five CE mark approved solutions include VUNO Med-BoneAge, VUNO Med-DeepBrain, VUNO Med-Chest X-Ray, VUNO Med-Fundus AI, and VUNO Med-LungCT AI.
The regulatory approval facilitates the commercialisation of the products in 27 EU member states, the Acceding countries along with EFTA states.
The company will also sell the products in Middle East, Asia, South and Central America, and African countries that recognise the CE mark.
VUNO said that the efficacy and safety of the new AI products was evaluated by a series of clinical researches, whore results have supported their regulatory approval.
VUNO CEO Hyun-Jun Kim said: “We have been taking proper measures to ensure that VUNO’s products obtain classification commensurate with their intended purposes as medical diagnostic supporting tools.
“In this sense, obtaining CE certification for all five products holds a great significance, and this will be able to accelerate our push for much anticipated global supply of VUNO Med series all around the world.”
Details of the five CE mark approved VUNO Meical AI solutions
VUNO Med – Fundus AI is designed to automatically detect various lesions from the fundus image and quickly classify them for diagnosis.
VUNO Med – LungCT AI will detect and quantify the pulmonary nodules prior to their progress into lung cancer, and automatically categorise the Lung-RADS to manage multiple pulmonary nodules.
By improving the screening function of chest X-rays, VUNO Med – Chest X-Ray helps in the detection of the most common thoracic findings and diseases through chest X-ray images that are difficult to be identified at an early stage.
The company’s first regulatory approved product VUNO Med – BoneAge will assist evaluation of bone age based on a child’s left hand X-ray image. The solution reduces diagnosis time and improves accuracy.
VUNO Med – DeepBrain is designed to segment brain regions using brain MRI data and measure the volumes of each region to provide atrophy volumetrics against normative database.
