Close
Digital Health & Ai Innovation summit 2026
APE 2026

AI-based cardiac arrest prediction software obtains approval as Innovative Medical Device in South Korea

Note* - All images used are for editorial and illustrative purposes only and may not originate from the original news provider or associated company.

Subscribe

- Never miss a story with notifications

- Gain full access to our premium content

- Browse free from any location or device.

Media Packs

Expand Your Reach With Our Customized Solutions Empowering Your Campaigns To Maximize Your Reach & Drive Real Results!

– Access the Media PackNow

– Book a Conference Call

Leave Message for Us to Get Back

Related stories

FDA May Scrutinize Medical Device Cybersecurity...

The scrutiny by the US Food and Drug Administration...

Recon DL Tool from GE HealthCare...

Pristina Recon DL tool from GE HealthCare which uses...

Abbott to Acquire Cancer Test Maker...

In a recent move, Abbott has gone ahead and...

South Korea-based medical AI solutions development company VUNO has obtained approval from the Ministry of Food and Drug Safety (MFDS) for its AI-based cardiac arrest prediction software, VUNO Med–DeepCARS as an Innovative Medical Device.

The software is specialized in predicting the risk of cardiac arrest and 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. The collection of data forms the basis for predicting the

likelihood of an emergency cardiac arrest situation occurring within the next 24 hours. 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.

THE LARGER TREND

VUNO also recently announced that it was selected to be part of a project, which is led by the National IT Industry Promotion Agency (NIPA) under the Ministry of Science and ICT (MSIT), to technologically demonstrate an AI-run system for medical image-based analysis and diagnosis.

The company plans to develop AI-based medical solutions that can meet the needs of the military environment and prove the accuracy and efficiency in medical

image analysis done by military hospitals and medical corps, in partnership with Wonju Severance Christian Hospital and Gachon University Gil Hospital.

In June, VUNO obtained CE Mark for five of its solutions: VUNO Med –BoneAge, VUNO Med –DeepBrain, VUNO Med -Chest X-Ray, VUNO Med –Fundus AI and VUNO Med –LungCT AI, Healthcare IT News reported.

ON THE RECORD

“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,” said Hyun-Jun Kim, CEO of VUNO.

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.”

Latest stories

Related stories

FDA May Scrutinize Medical Device Cybersecurity More in 2026

The scrutiny by the US Food and Drug Administration...

Recon DL Tool from GE HealthCare Receives a PMA

Pristina Recon DL tool from GE HealthCare which uses...

Abbott to Acquire Cancer Test Maker for Around $21 Billion

In a recent move, Abbott has gone ahead and...

New Policy to Boost Medical Device Industry in China

Beijing has gone on to release a new policy...

Subscribe

- Never miss a story with notifications

- Gain full access to our premium content

- Browse free from any location or device.

Media Packs

Expand Your Reach With Our Customized Solutions Empowering Your Campaigns To Maximize Your Reach & Drive Real Results!

– Access the Media Pack Now

– Book a Conference Call

Leave Message for Us to Get Back

Translate »