Applications and prospects of artificial intelligence in wound healing

Wound healing is a critical aspect of clinical treatment, particularly in the management of complex wounds, including burns, diabetic foot ulcers (DFU). In recent years, artificial intelligence (AI) technologies—especially machine learning (ML), deep learning (DL), and computer vision (CV)—have achieved significant breakthroughs in medical image analysis, thereby advancing automated wound assessment, precision treatment planning, and dynamic healing surveillance. AI enables rapid identification of wound boundaries and infection risks across various wound types, enhancing the objectivity and efficiency of clinical evaluations. Additionally, personalised data analytics facilitate informed treatment decisions, optimise resource allocation, and improve healing outcomes. This review systematically summarises the current applications of AI in both acute and chronic wound care, including wound assessment, individualised treatment decision support, and healing prediction, highlighting its unique advantages in enhancing diagnostic accuracy and real-time monitoring. Looking forward, with the integration of multimodal data and the advancement of intelligent hardware, AI is poised to play an increasingly pivotal role in wound management, driving the evolution of smart healthcare to a higher level.