VUNO Inc., South Korean artificial intelligence (AI) developer, announced that VUNO Med®–DeepCARS™, its AI-based cardiac arrest prediction software, proudly became an Innovative Medical Device designated by the Ministry of Food and Drug Safety (MFDS). Indeed, it is yet another achievement that VUNO made immediately after VUNO Med®-Fundus AI™, AI-based fundus screening solution, gained the honor of becoming the nation’s first-ever Innovative Medical Device by MFDS in July.
The MFDS was unanimously elected to be the first chair of Artificial Intelligence Medical Devices (AIMDs) at the International Medical Device Regulators Forum (IMDRF) held on June 25. All the credit goes to the agency’s continuous effort to set the path for the leading regulatory framework of AI-based medical devices by establishing guidelines for approval and review of AI-based medical devices in 2017 for the first time in the world.
With the MFDS taking at the helm, the Innovative Medical Devices are classified and designated among candidates that excel in safety and effectiveness compared to conventional medical apparatuses and treatments. The following is included in the evaluation criteria: technological intensity and pace of technological innovation (technological innovation); enhancement in safety and effectiveness compared to the existing medical devices (performance); and economic, social, and technological ripple effect (contribution to the public good and industrial value).
Hyun-Jun Kim, CEO of VUNO, said, “VUNO Med®–DeepCARS™ makes predictions about cardiac arrest based on a variety of vital signs to allow for early detection and swift response. Obviously, this epoch-making solution will serve as a game changer once it comes into clinical use.” He added, “VUNO is dedicated to pioneer groundbreaking AI-based solutions across various medical fields from deep learning-based solutions using medical images to technologies regarding vital signs.”
About VUNO Med®–DeepCARS™
VUNO Med®–DeepCARS™, AI-based medical software, is specialized in predicting the risk of cardiac arrest. The solution performs a medical analysis of vital signs of patients in general wards stored in the electronic medical records (EMR) including heart rate, respiratory rate, blood pressure, and body temperature. Such a collection of data does the basis for predicting the likelihood of an emergency cardiac arrest situation occurring within the next 24 hours. The clinical testing is underway for VUNO Med®–DeepCARS™ based on a clinical trial plan approved by the MFDS in June.
According to a research paper published in Critical Care Medicine (CCM) in February, VUNO Med®–DeepCARS™ had a level of sensitivity twice as high as Modified Early Warning Score (MEWS) – a conventional way of cardiac arrest prediction – for the same number of alarms. Added to this, VUNO Med®–DeepCARS™ showed a decrease of 59.6% in the total number of alarms for the same level of sensitivity, thus proving a low false alarm rate. Thus, expectations are growing that the implementation of VUNO Med®–DeepCARS™ in the forefront of medical care will not only lessen medical professionals’ fatigue from false alarms but also help prevent against cardiac arrest among inpatients by making considerably accurate predictions.