Artificial Intelligence for Postoperative Wound Monitoring: An Integrative Review of Digital Innovation and Clinical Feasibility

Abstract

Artificial intelligence (AI) has transformative potential in postoperative wound care through precise, automated, and timely wound assessment, yet specific applications to surgical wounds remain relatively unexplored compared to chronic wound care. This integrative review critically assesses the state-of-the-art in AI-driven postoperative wound monitoring, highlighting significant advancements, existing limitations, and opportunities for future development. Following an extensive literature search of PubMed, Google Scholar, and Medline, we identified 118 relevant articles meeting stringent inclusion criteria. Our analysis underscores the critical need for large-scale, standardized datasets, explainable AI frameworks, and robust clinical validation studies. By evaluating AI technologies—such as deep learning, wearable biosensors, mobile applications, and natural language processing—we propose a roadmap for integrating advanced AI methods into surgical practice, aiming ultimately to enhance clinical outcomes and patient care.