Solution system technology that predicts ulcer stage from images and recommends appropriate bandaging methods was developed by Korean researchers.
Professor Kang Mira from the Medical and Health Department of Samsung Hospital and the research team Shim Soyeon, Kim Minkyung, Song Mira from the Nursing Department collaborated with Fine Healthcare and developed ‘Skinex’, a solution system AI-based ulcer stage prediction method. This was announced at the 2022 Global Conference organized by the Healthcare Information and Management Systems Society (HIMSS).
Skinex (Skin Explainable AI) will scan images of the ulcer area, classify them into stages (stage 1 to 4, unclassified, deep tissue damage), predict the level of tissue damage over time. Realize and recommend appropriate bandages for treatment when information about skin conditions is entered into the system.
Approximately 10,000 images of bed sores collected through barcoded point of care (BPOC) were labeled and developed by three nurses with over 10 years of experience, providing a solution that is reliable and high precision.
With the introduction of Skinex, it is now expected to provide ‘high quality’ care for patients with ulcers, improving accuracy by minimizing errors in the assessment of stages ulcers, as well as providing complete information on bandaging materials.
Now, after 13 inpatient departments participated in the pilot program, the program plans to enhance the solution by adding additional functions and data collection necessary for inpatient nursing. bedridden, while expanding into the global market.
Professor Kang Mira, who supervised this research, said: “The AI-based management solution system to predict ulcer stage will provide useful guidance for nurses to provide services. medical care while reducing work burden by providing real-time ulcer staging information and treatment guidance to nurses who need to manage bedridden patients.”
Furthermore, nurse Shim Soyeon, who co-developed the solution system, stated: “The solution system is installed in the hospital’s mobile devices, so regardless of whether the nurse is new or experienced , can all take advantage of the system to their advantage.”
