AI-driven Management of Wound Care Workflows

DOI: https://doi.org/10.62517/jmhs.202405303

Author(s)

Min Shen1,#, Shuwen Han2,#, Zeyang Feng3,#, Xuecan Yang1,4, Laurent Peyrodie5, Jean-Marie Niang1,6, Zefeng Wang3,4,5,6,*

Affiliation(s)

1ASIR, Institute - Association of Intelligent Systems and Robotics, Paris, France 2Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, Zhejiang, China 3College of Information Engineering, Anding Honors College, Huzhou University, Huzhou, Zhejiang, China 4IEIP, Institute of Education and Innovation in Paris, Paris, France 5ICL, Junia, Université Catholique de Lille, LITL, F-59000 Lille, France 6Sino-Congolese Foundation for Development, Brazzaville, Republic of the Congo *Corresponding Author. #These authors contributed equally to this work.

Abstract

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.

Keywords

Artificial Intelligence; Wound Care Workflows; Smart Healthcare; Medical Service; Resource Management

References

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