Huinno executives and Johns Hopkins researchers pose after signing a joint research agreement on an AI tool for early prediction of patient deterioration. (Courtesy of Huinno)
Korean digital health company Huinno is working with researchers at Johns Hopkins University to develop and test an AI tool designed to detect early signs of deterioration in hospital ward patients.
The project will focus on general wards, where vital signs are often checked only every few hours and existing early warning systems can produce frequent false alarms, adding to staff workload.
Huinno said the research will use its real-time inpatient monitoring system, MEMO Cue, and its AI-based clinical deterioration prediction tool, Vital PICASO, to analyse patient data and help medical staff intervene earlier.
The company said the system is designed to analyse patient data in real time and help medical staff intervene earlier when a patient’s condition begins to worsen.
The collaboration will be led by a Johns Hopkins team associated with Kunihiro Matsushita, a professor at the university’s Bloomberg School of Public Health and School of Medicine. Matsushita’s work includes epidemiology, cardiovascular disease, risk prediction and research using electronic health records.
Huinno said Johns Hopkins researchers will take part in a multidisciplinary task force involving specialists in medical AI, electrophysiology, electronic health records and precision medicine.
Vital PICASO, developed by Huinno's subsidiary Huinno AIM, is designed to analyse vital-sign data from general ward patients and predict risks including hypotension, hypoxia and cardiac arrest. It was designated an innovative medical device by Korea’s Ministry of Food and Drug Safety (MFDS) last year.
Kim Ji-hye
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