State of the art of the automatized characterization of chronic wound patterns

Currently, medicine has experienced a growing interest in the use of artificial intelligence (AI) combined with other information technologies, for the interpretation, classification and prediction of pathologies and injuries from medical images in an automated or semi-automated way because they contribute, among other tasks, to diagnose and monitor patients. This work is a systematic review of five databases exploring projects, between 2018 and 2024, that have used Artificial Intelligence techniques like deep learning and machine learning in the classification, segmentation, and detection of wound images. The results suggest that these technologies in the medical field can reduce workload, standardize diagnosis, improve accuracy and treatment, and positively impact the quality of patient care. The management of chronic wounds is complex due to their etiology and the lack of visual capacity of the medical professional. For this reason, the automation of these processes promises to have the potential to significantly improve medical care, and consequently, affect the quality of patients’ lives.