{"title":"Explainable Artificial Intelligence in Deep Learning Neural Nets-Based Digital Images Analysis","authors":"A. N. Averkin, E. N. Volkov, S. A. Yarushev","doi":"10.1134/s1064230724700138","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>This review shows the capabilities of artificial intelligence (AI) in the analysis of digital images in the field of medicine using convolutional neural networks of deep learning (DL). A new generation of AI systems is described with an explanation of decision-making algorithms to the user—explainable artificial intelligence (XAI). The taxonomy of the methods of explanation and the description of the methods themselves are given. The need to use XAI in classification tasks is substantiated on the example of ophthalmic diseases. The components of DL methods used in the reviewed works (neural network architecture, accuracy, characteristics of data sets) and XAI (methods of explanation, criteria for the accuracy of explanation) are studied. As an example, the problem of recognizing two of the most commonly diagnosed eye diseases is considered: diabetic retinopathy and glaucoma by artificial neural networks.</p>","PeriodicalId":50223,"journal":{"name":"Journal of Computer and Systems Sciences International","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer and Systems Sciences International","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1134/s1064230724700138","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
This review shows the capabilities of artificial intelligence (AI) in the analysis of digital images in the field of medicine using convolutional neural networks of deep learning (DL). A new generation of AI systems is described with an explanation of decision-making algorithms to the user—explainable artificial intelligence (XAI). The taxonomy of the methods of explanation and the description of the methods themselves are given. The need to use XAI in classification tasks is substantiated on the example of ophthalmic diseases. The components of DL methods used in the reviewed works (neural network architecture, accuracy, characteristics of data sets) and XAI (methods of explanation, criteria for the accuracy of explanation) are studied. As an example, the problem of recognizing two of the most commonly diagnosed eye diseases is considered: diabetic retinopathy and glaucoma by artificial neural networks.
期刊介绍：
Journal of Computer and System Sciences International is a journal published in collaboration with the Russian Academy of Sciences. It covers all areas of control theory and systems. The journal features papers on the theory and methods of control, as well as papers devoted to the study, design, modeling, development, and application of new control systems. The journal publishes papers that reflect contemporary research and development in the field of control. Particular attention is given to applications of computer methods and technologies to control theory and control engineering. The journal publishes proceedings of international scientific conferences in the form of collections of regular journal articles and reviews by top experts on topical problems of modern studies in control theory.
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