Deep Learning for Medical Anomaly Detection – A Survey

Machine learning–based medical anomaly detection is an important problem that has been extensively studied. Numerous approaches have proposed across various application domains and we observe several similarities these distinct applications. Despite this comparability, a lack of structured organisation diverse research applications such their advantages limitations can be The principal aim survey to provide thorough theoretical analysis popular deep learning techniques in detection. In particular, contribute coherent systematic review state-of-the-art techniques, comparing contrasting architectural differences as well training algorithms. Furthermore, comprehensive overview model interpretation strategies used interpret decisions. addition, outline the key existing propose directions for further investigation.