Application of artificial intelligence methodologies to chronic wound care and management

As the number of hard-to-heal wound cases rises with the aging of the population and the spread of chronic diseases, healthcare professionals struggle to provide safe and effective care to all their patients simultaneously. Accurately predicting wound healing trajectories is difficult for wound care clinicians due to the complex and dynamic processes involved in wound healing. Wound care teams capture images of wounds during clinical visits generating big datasets over time.We have witnessed rapid advancement in technology over the last few decades. With the advent of artificial intelligence (AI), newer avenues have opened for researchers. Electronic Medical Records, or EMRs, have recently been incorporated into the health care system. This has allowed ease of accessibility to patient information. The availability of massive amounts of clinical data and robust programming has increased healthcare professionals' interest in AI's potential role in the healthcare industry. With increasing availabilities of massive data (wound images, wound-specific electronic health records, etc.) AI-based digital platforms will play a significant role in delivering data-driven care to people suffering from debilitating chronic wounds. Developing novel AI systems can help clinicians diagnose, assess the effectiveness of therapy, and predict healing outcomes. Another significant development that emerged from the findings is AI-based remote consultation systems utilizing smartphones and tablets for data collection and connectivity. In addition to showing promising results in wound healing prediction, artificial intelligence might also become a viable tool for wound assessment.In this article, we will attempt to briefly review current literature discussing AI in critical care medicine and analyze its future utility based on prevailing evidence.