The AI model for prediction of the risk of falls reflects more than 20 factors. (Yonhap)
SEOUL, Sept. 16 (Korea Bizwire) — A new artificial intelligence (AI) model has been developed using big data to predict the possibility of patients suffering from falls or bedsores on a real-time basis.
The Hallym University Medical Center announced on Tuesday that it had developed a new AI model that can predict the possibility of patients suffering from falls or bedsores.
The new AI model was developed based on the analysis of 280,000 cases of bedsores and 160,000 cases of falls accumulated over the past five years.
The AI model for prediction of the risk of falls reflects more than 20 factors, including the patient’s basic information, the injection of drugs that heighten the risk of falls, and the use of anticoagulant drugs.
The AI model for prediction of the risk of bedsores reflects not only patient data such as the degree of the patient’s recognition of sense, the degree of activity and mobility and their nutritional state, but also external factors such as humidity and frictional force.
Unlike existing tools that can check the possibility of patients suffering from falls or bedsores only during hospitalization or during a specific time after surgery, the newly-developed AI model can identify this risk anytime on a real-time basis.
When healthcare workers search for patient information, for example, the AI model can calculate the possibility of patients suffering from falls or bedsores and display the information on the screen.
“The AI model enables healthcare workers to instantly check the possibility of patients suffering from falls or bedsores that changes on a real-time basis depending on what medical treatment is used,” said Lee Kang-Il, head of the Medical Information Team at Hallym University Medical Center.
J. S. Shin (js_shin@koreabizwire.com)
