AI-driven Management of Wound Care Workflows

Wound care is a critical aspect of healthcare, particularly in managing chronic and complex wounds, which require multifaceted approaches involving accurate assessment, appropriate intervention, continuous monitoring, and efficient resource allocation. The advent of artificial intelligence (AI) offers innovative solutions to these long-standing challenges. This study aims to explore how AI optimizes and manages wound care workflows by leveraging publicly available data and existing literature. Key findings indicate that AI chatbots demonstrate high accuracy in identifying suitable treatment plans, matching the decisions of experienced wound care specialists in 91% of cases. AI image analysis technologies, such as U-Net and Efficient Net, significantly enhance wound boundary delineation, improving wound dimension measurement and healing progress monitoring. Data-driven AI practices, through 3D modeling and workflow automation, enhance diagnostic accuracy and treatment efficacy, thereby improving wound care resource management efficiency. In conclusion, the integration of AI in wound care substantially enhances clinical workflows and patient care quality while reducing costs.