Department of Artificial Intelligence, Lviv Polytechnic National University, Kniazia Romana str., 5, Lviv 79905, Ukraine.
Math Biosci Eng. 2022 Jul 7;19(10):9769-9772. doi: 10.3934/mbe.2022454.
Modern medical diagnosis, treatment, or rehabilitation problems of the patient reach completely different levels due to the rapid development of artificial intelligence tools. Methods of machine learning and optimization based on the intersection of historical data of various volumes provide significant support to physicians in the form of accurate and fast solutions of automated diagnostic systems. It significantly improves the quality of medical services. This special issue deals with the problems of medical diagnosis and prognosis in the case of short datasets. The problem is not new, but existing machine learning methods do not always demonstrate the adequacy of prediction or classification models, especially in the case of limited data to implement the training procedures. That is why the improvement of existing and development of new artificial intelligence tools that will be able to solve it effectively is an urgent task. The special issue contains the latest achievements in medical diagnostics based on the processing of small numerical and image-based datasets. Described methods have a strong theoretical basis, and numerous experimental studies confirm the high efficiency of their application in various applied fields of Medicine.
由于人工智能工具的快速发展,患者的现代医学诊断、治疗或康复问题达到了完全不同的水平。基于各种卷的历史数据的机器学习和优化方法以自动化诊断系统的准确和快速解决方案的形式为医生提供了重要支持。它显著提高了医疗服务的质量。本特刊讨论了在数据集较小的情况下的医疗诊断和预后问题。这个问题并不新鲜,但现有的机器学习方法并不总是表现出预测或分类模型的充分性,尤其是在有限的数据情况下实施训练程序时。这就是为什么改进现有的和开发新的人工智能工具,使其能够有效地解决这个问题是一个紧迫的任务。本特刊包含了基于小数值和基于图像的数据集处理的最新医学诊断成果。所描述的方法具有坚实的理论基础,并且大量的实验研究证实了它们在医学的各个应用领域中的高效应用。