Artificial neural networks and computer vision in medicine and surgery

Introduction: Artificial neural networks are becoming an essential technology in data analysis, and their influence is starting to permeate the field of medicine. Experimental surgery has been a long-term subject of study of our lab; this is naturally reflected in our interest in other areas of modern technologies including artificial neural networks and their advancements. In the current issue, we would like to explore this aspect of technical progress. The main goal is to critically evaluate the strengths and weaknesses of artificial neural network technology concerning its use in clinical and experimental surgery. Methods: The article is focused on in-silico modeling, particularly on the potential of neural networks in terms of image data processing in medicine. The text briefly summarizes the historical development of deep learning neural networks and their basic principles. Furthermore, basic taxonomy tasks are presented. Finally, potential learning problems and possible solutions are also mentioned. Results: The article points out various possible uses of artificial neural networks in biological applications. Several biomedical applications of artificial neural networks are u