Journal of Intensive and Critical Care Nursing

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Novelties in Artificial Intelligence Recognition and Diagnosis Technology in Pressure injury

Joint Event on 2nd European Nursing Congress & International Conference on Clinical Nursing & Practice
October 24-25, 2019 | Zurich, Switzerland

Wei Luan,Zhu Z

Renji Hospital Affiliated to Medical School of Shanghai Jiaotong University, China

Keynote : J Intensive Crit Care Nurs

Abstract:

Artificial intelligence recognition and diagnosis technology of pressure injury is mainly used in clinical auxiliary diagnosis system. By using the image recognition technology of artificial intelligence, the algorithm with higher parallel performance is designed and the special language for parallel image processing is developed to scientifically and rapidly identified and diagnosed pressure injury. Accordingly, the clinical assistant diagnosis system can provide nurses with the most possible diagnosis of pressure sore nursing and recommend nursing measures. The application of artificial intelligence technology has achieved great success in the field of image diagnosis. Therefore, it is also very reliable and safe to be used in the field of pressure injury. Such artificial intelligence recognition and diagnosis technology can greatly improve the correct diagnosis rate of pressure ulcer and the work efficiency of nurses. Especially in remote areas, there is a lack of wound stomatologists or licensed nurses, and family members of patients can also take photos and upload them to the system. Nurses can make remote diagnosis and guidance.

Biography:

Wei Luan, Master of Nursing Science, is the director of Nursing Department and senior nursing scholar of the Southern Hospital of Renji Hospital Affiliated to Medical College of Shanghai Jiaotong University. She is a member of the editorial board of several Chinese periodicals and the professional committee of geriatric care of China Geriatric Health Association. Two improved pressure sore measuring tools invented by her have been patented for utility models.

E-mail: luanwei_renji@126.com

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