AI-assisted design and application of wound dressings

• This study addresses the critical challenge of managing complex wound microenvironments, particularly in chronic and hard-to-heal wounds such as diabetic ulcers and pressure sores. By integrating artificial intelligence (AI) into the design, manufacturing, and monitoring of wound dressings, we propose a transformative approach that overcomes the limitations of traditional methods. Our work demonstrates how AI-driven strategies—including machine learning (ML) models for high-throughput screening of hydrogel formulations, dynamic drug release optimization, and real-time wound parameter analysis—enable personalized, adaptive, and intelligent wound care solutions. • The significance of this research lies in three key contributions:. • Innovation in Design: AI algorithms analyze clinical and biochemical data to predict optimal material compositions and structural configurations, improving dressing functionality by up to 15 % in exudate absorption and 10 % in healing rates compared to conventional methods. • Precision Manufacturing: AI-assisted 3D printing and automated quality control ensure consistency in production, reducing material waste by 20 % and enabling rapid prototyping of patient-specific dressings. • This work bridges the gap between AI technology and clinical wound management, offering scalable solutions for personalized medicine. By advancing our understanding of wound pathophysiology and optimizing therapeutic delivery, AI-integrated dressings have the potential to reduce healthcare costs, minimize amputations in diabetic patients, and improve quality of life for millions globally. Future applications may extend to 4D-printed adaptive materials and systemic immune modulation, positioning AI as a cornerstone of next-generation wound care. The rising prevalence of wounds from various causes has highlighted the challenge of addressing their complex microenvironments. Conventional design and manufacturing methods of dressings face difficulties in achieving optimal performance and often fall short of meeting specific needs, emphasizing the urgent demand for functional alternatives. With advancements in science and technology, artificial intelligence (AI) has emerged as a powerful tool to address these issues. AI offers the potential to optimize dressing design and fabrication, enabling precise targeting of complex wound environments. This review provides an overview of AI-assisted wound dressing technologies, focusing on their design methodologies and applications. It categorizes dressings by material types and explores existing AI-assisted strategies for improving their functionality. We also discuss the limitations of traditional approaches, the potential of AI to overcome these barriers, and future directions for integrating AI into wound care. In conclusion, the development of AI-assisted wound dressings is expected to transform the field. It will enhance our understanding of wound-specific requirements, improve dressing functionality, and support personalized treatment strategies, ultimately paving the way for clinical applications.