Application of Artificial Intelligence in Wound and Tissue Repair: Diagnosis, Prevention, Treatment

Introduction: A wound is any type of injury in the body that causes damage to skin tissues and disrupts the integrity of the skin. there are different methods for treating each wound. artificial intelligence can be used as a useful tool to investigate the condition of these wounds and provide reliable recommendations to doctors. The purpose of this study is to identify the applications of artificial intelligence in the prevention, diagnosis and treatment of wounds and tissue repair.Methods: This review was conducted in ۲۰۲۳. We searched PubMed, Web of Science, and Embase scientific databases, based on the combination of related Mesh terms. The articles selection process was based on Preferred Reporting Items for Reviews. Articles selection was done by using the inclusion and exclusion criteria. Data gathering was done using a data extraction form.Results: Artificial intelligence can help in diagnosing and differentiating the types of wounds and their treatment. By using machine learning algorithms and deep neural networks, artificial intelligence systems are able to analyze and recognize the type of wounds. For this purpose, an artificial intelligence system can use images of the wound (such as photos and scans) and, combining the patient's history, recognize the type of wound and its severity. This information helps doctors plan the right treatment for each patient. In addition, artificial intelligence systems can provide guidance and recommendations on appropriate treatment methods for each type of wound. This includes tips on cleaning the wound, using specific products and materials for wound healing, and scheduling treatment.Conclusion: Artificial intelligence can play an important role in the diagnosis, differentiation and treatment of wounds using machine learning algorithms and deep neural networks and help doctors prepare accurate and appropriate treatment plans. It is recommended to use the artificial intelligence to help predict the best method of diagnosis and treatment in tissue repair