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Yonsei, AITRICS to establish AI-based emergency prediction system
  • By Lee Han-soo
  • Published 2019.03.08 16:09
  • Updated 2019.03.08 16:09
  • comments 0

Yonsei University Health System (YUHS) said Thursday that it has signed an agreement with AITRICS to establish an artificial intelligence (AI)-based emergency prediction system.

Yonsei University Health System President and CEO Yoon Do-heum (left) and AITRICS CEO Yoo Jin-kyu hold up the agreement at Yonsei University Health System in Sinchon, Seoul, Wednesday.

AITRICS is an AI specialized company that develops a system predicting early diseases and risks in various medical environments based on the latest AI-based technology. The company has developed AI technology that can identify danger signals such as sepsis and cardiac arrest before the situations for patients in intensive care and hospital ward.

YUHS and AITRICS plan to build a predictive emergency system that can predict accidental deaths of critically ill admitted patients through a pre-AI Medical response.

Under the agreement, YUHS will verify the effectiveness and safety of the program by applying the technology to its clinical practices such as intensive care rooms, wards, and emergency rooms.

Through AI development, the two institutes anticipate that they will achieve safe and efficient patient management by recognizing emergency signals for patients with ICU and ward inpatients in advance. Also, with the completion of the system, both parties expect that the workload of the ICU team, the rapid response team, and emergency room medical staff will be partially resolved.

YUHS plans to apply this system to Yongin Dongbaek Hospital, scheduled to open in 2020.

“The quality of medical care can be improved by the program that can cope with the emergency of the inpatients through medical AI,” project leader Professor Chung Kyung-soo said. “More patients will be treated safely in the ICU, ward, and emergency room in the future.”

AITRICS CEO Yoo Jin-kyu also said, “To apply medical artificial intelligence to the actual field, clinical validation should be activated to ensure safety and effectiveness. Through this collaboration, we hope to prove the medical value and increase the credibility of medical artificial intelligence.”


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