Abstract
The object of research is the process of using the technology of artificial intelligence and computer vision in the medical field. The subject of the study is the introduction of the neural network in diagnostic information systems and its collaboration with the mobile application iOS for the diagnosis of skin lesions and diseases. The property of neural networks is their ability to learn based on environmental data and as a result of learning to increase their productivity. After analyzing the existing methods for further implementation in the software product for neural network training, the method of parallelization of sampling training was chosen. One of the most problematic places is the task of diagnostics in the medical field, which requires, along with expert solutions, the use of modern approaches based on artificial intelligence and computer vision. Through the use of artificial intelligence and computer vision, experts try to assess the patient's condition and accurately diagnose, because the human factor is always present in the medical field, so the use of artificial intelligence aims to improve the quality of patient diagnosis. Research methods include computational experiments, comparative analysis of results, object-oriented programming. The study used computer vision techniques, which include methods for obtaining, processing, analyzing and understanding digital images. A neural network for the analysis of injuries and diseases of the skin has been trained and an information system for diagnosing and monitoring the health of the skin has been implemented by creating a mobile application based on iOS. The results of the implementation can give users the opportunity to monitor the condition of their skin, receive recommendations for its preventive treatment, provide advice on the treatment or prevention of diseases, provide information literature
Highlights
The global expansion of mobile devices into the consumer market and the annual technological capabilities of mobile devices today provide an opportunity to create and maximize the processes of translating our usual actions and operations in application to mobile operating systems, as well as to apply mobility and capabilities in various areas of our lives [1].Such ideas and their implementation provide hardware updates for mobile devices, such as: improving the camera, increasing the amount of RAM and physical memory of devices, etc
It was possible to see a steady trend of turning mobile devices and mobile applications into a digital assistant who books us tables in a restaurant, on request can order us food from the supermarket, informs us about our work calendar, meeting, the birthday of a family member and so on [2]
The list of tasks includes determining the diagnosis and nature of the skin disease to assist the doctor. It can be the provision of the widest possible information about the course of the disease or the provision of recommendations for disease prevention based on the climate of the region of residence, age. Such tasks will be inextricably linked to artificial intelligence and computer vision technologies and may be available to every smartphone user
Summary
The object of research is the process of using the technology of artificial intelligence and computer vision in the medical field. The subject of the study is the introduction of the neural network in diagnostic information systems and its collaboration with the mobile application iOS for the diagnosis of skin lesions and diseases. One of the most problematic places is the task of diagnostics in the medical field, which requires, along with expert solutions, the use of mo dern approaches based on artificial intelligence and computer vision. A neural network for the analysis of injuries and diseases of the skin has been trained and an information system for diagnosing and monitoring the health of the skin has been implemented by creating a mobile application based on iOS. Development of neural network and application of computer vision technology for diagnosis of skin injuries and diseases.
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