In the last few years, technologies based on artificial intelligence have advanced rapidly, and over the past two decades, we have witnessed great progress in artificial intelligence and its application. Some of the earliest work in the successful application of artificial intelligence occurred precisely in the medical context. This paper explains the basics of artificial intelligence, machine, and deep learning. An overview of artificial intelligence in the medical field and the advantages of its use in various fields of medicine is given. The area of computer vision is explained with an emphasis on object detection. The paper describes machine learning algorithms, neural networks, artificial neural networks, and convolutional neural networks. As part of this thesis, was developed an application that classifies surgical instruments. The following development tools were used in the development of the application: Cloud Annotations, Colaboratory, and Node-RED. The TensorFlow machine learning library was used for model training and the Python programming language. The machine learning model in TensorFlow.js format is integrated with a graphical interface, that is created using the development tool Node-RED and the JavaScript programming language. The application allows the user to take a photo directly or load the image from a computer to recognize it. The application recognizes five different surgical instruments: curved surgical scissors, flat surgical scissors, scalpel, surgical tweezers, and forceps.