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Proceedings of the Southwest State University. Series: IT Management, Computer Science, Computer Engineering. Medical Equipment Engineering最新文献

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A System for Collecting and Evaluating Load Information about Bioelectric Signals of the Muscular Apparatus of the Foot of a Person with Cerebral Palsy 收集和评估脑瘫患者足部肌肉装置生物电信号负载信息的系统
S. M. Yatsun, A. Rukavitsyn, E. Politov
The purpose of the research is to develop a system of biomechanical investigation of the volume of movement in the foot and ankle joint for the diagnosis of patients with cerebral palsy in assessing the quality of rehabilitation measures. The process of creating a computer diagnostic system for patients with impaired motor functions of the lower extremities, which is equipped with special bio-measuring devices provided with specialized algorithms for processing the information obtained, is investigated due to the need for scientific research aimed at developing methods and tools for a comprehensive assessment of the results of physical rehabilitation using biomedical indicators.Methods of kinematic analysis of movements in the ankle joint were used, dynamic and static analyses of the forces of the supporting reactions of the foot of the lower extremities were carried out.Results. A motion detection system based on an electronic goniometer implemented on the basis of a B10K resistive potentiometer has been developed. The determination of the absolute rotation angles of the links of the diagnostic system was carried out using the MMA7361 acceleration sensor, which contains three micromachine capacitors mounted on one silicon plate. In the course of research, changing the capacitances of micromachine capacitors makes it possible to fix the recorded value in each direction. Signals passing through low-frequency filters and temperature compensation cascades are sent to the corresponding outputs X, Y and Z. The obtained angulograms allow us to evaluate the gait of the studied patient in two classes ‒ normal and in the presence of pathology.Conclusion. A system for the formation and evaluation of bioelectric signals obtained using the muscular apparatus of the foot of patients with cerebral palsy, assembled on the platform of the Arduino UNO control board and a generalpurpose personal computer, has been developed. The developed system makes it possible to register bioelectric signals with their subsequent processing using a personal computer and making diagnostic decisions.
该研究的目的是开发一套足踝关节运动量生物力学调查系统,用于诊断脑瘫患者,评估康复措施的质量。为下肢运动功能受损的患者创建计算机诊断系统的过程是在科学研究的需要下进行调查的,该系统配备了特殊的生物测量设备,并提供了处理所获信息的专门算法,目的是开发使用生物医学指标全面评估身体康复结果的方法和工具。在 B10K 电阻式电位计的基础上开发了电子动态关节角度计运动检测系统。诊断系统各链接的绝对旋转角度是通过 MMA7361 加速度传感器确定的,该传感器包含三个安装在一块硅板上的微型机械电容器。在研究过程中,改变微型机械电容器的电容值可以固定每个方向的记录值。通过低频滤波器和温度补偿级联的信号被发送到相应的 X、Y 和 Z 输出端。获得的角度图使我们能够对所研究病人的步态进行两级评估--正常和存在病变。在 Arduino UNO 控制板和通用个人电脑的平台上,开发了一套利用脑瘫患者足部肌肉装置获得的生物电信号的形成和评估系统。所开发的系统可以对生物电信号进行注册,然后使用个人电脑对其进行处理,并做出诊断决定。
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引用次数: 0
Particle Size Analysis of Nanopowders Using Neural Networks and Electron Microscopy 利用神经网络和电子显微镜分析纳米粉体的粒度
R. A. Tomakova, D. V. Psarev, Y. A. Neruchev, V. A. Starkov
The purpose of the research is to develop an application capable of automatically determining the particle size distribution of nanopowder using neural network technology in order to simplify the process of preparing documentation during its manufacture.Methods. To determine the physical properties of nanopowders during their fabrication, it is necessary to analyze the particle size distribution. A methodology for determining the size distribution of nanopowder particles based on light neural networks is proposed. Images obtained by electron microscopy are used for processing, which allows to speed up the preparation of manufactured powders for sale. The dataset collected for training contains real images of samples of different powders, augmented data and generated images. The Python language, LabVIEW graphical programming environment, YOLO convolutional neural network and various Python language libraries were used in the development.Results. The study resulted in a model trained on the collected dataset that is capable of recognizing particles in images. A software interface was created to work with the model to analyze nanopowder samples.Conclusion. The developed application allows to automatically determine the size of each powder particle on the basis of the obtained images, as well as to build graphs of their size distribution. This greatly simplifies the work of nanopowder producers and facilitates the preparation of the necessary documentation for the produced product.
本研究的目的是开发一种能够利用神经网络技术自动确定纳米粉体粒度分布的应用程序,以简化纳米粉体制造过程中的文件编制过程。为了确定纳米粉体在制造过程中的物理特性,有必要对其粒度分布进行分析。本文提出了一种基于光神经网络确定纳米粉体颗粒粒度分布的方法。利用电子显微镜获得的图像进行处理,可以加快制备用于销售的粉末的速度。为训练而收集的数据集包含不同粉末样品的真实图像、增强数据和生成图像。开发过程中使用了 Python 语言、LabVIEW 图形编程环境、YOLO 卷积神经网络和各种 Python 语言库。研究结果显示,在收集的数据集上训练出的模型能够识别图像中的颗粒。研究还创建了一个软件界面,用于与该模型配合分析纳米粉体样本。所开发的应用程序可以根据所获得的图像自动确定每个粉末颗粒的大小,并绘制颗粒大小分布图。这大大简化了纳米粉体生产商的工作,便于为所生产的产品准备必要的文件。
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引用次数: 0
Specialists Training for the Radiation Type of Non-Destructive Testing Based on Digital Technologies 基于数字技术的辐射类无损检测专家培训
V. Kuvshinnikov, E. Kovshov
The purpose of research is the development of application software, including VR-technologies, to increase the number of trained specialists in radiation type of nondestructive testing by reducing the per capita load on radiographic laboratories while maintaining the amount of practical training, acquired competencies and formed relevant professional skills.Methods. Prerequisites for virtualization of the process of training specialists in nondestructive testing of structural materials and fabricated products are defined. The main factors of demand for industrial radiography simulator in relation to the practical part of the educational cycle on radiation type of nondestructive testing are considered. As a result of the analysis the most significant aspects of practical training, available for their virtual realization, are singled out. The results of software implementation of mathematical models of physical and physicochemical processes of ionizing radiation, attenuation and absorption of penetrating radiation within the scope of digital twin of radiographic image generation as a result of simulation of the technological process of radiation type of nondestructive testing are presented.Results. Performed practical implementation of didactic materials in the form of hardware and software VR-simulator as part of digital educational environment to solve the problems of training, retraining, preparation for certification of personnel and providing admission of specialists to work on radiation type of nondestructive testing at facilities. Physical and technological aspects are analyzed, modeling, algorithmization and software implementation of VR-simulator are performed. A comprehensive approach to the creation of a learning environment with the use of digital technologies is presented. Considered are the main components, their goals and objectives. The structure of a practical lesson and illustrations of the training process in a virtual environment are given. The results of approbation of training programs with integration of classes in VR-simulator of industrial radiography have shown that the total time of practice of trainees increases by 40-55% with simultaneous reduction of per capita radiographic laboratory load by more than 25%. The main directions of development and scaling of software and hardware solution using VR-technologies are given.Conclusion. The developed and tested hardware-software solution together with the results of scientific research suggests the possibility of application and development directions of the digital educational system with VR-environment. The proposed approach application will allow to reduce environmental and biomedical risks by reducing the requirements to safety of training with the use of software and hardware solution. Automation of testing task generation and knowledge control procedures on the basis of software tools and mathematical models application, including methods of artificial intelligence, wil
研究目的是开发包括虚拟现实技术在内的应用软件,通过减少放射实验室的人均负荷,同时保持实践培训量、获得的能力和形成的相关专业技能,增加接受过辐射类无损检测培训的专家人数。确定了结构材料和制造产品无损检测专家培训过程虚拟化的前提条件。考虑了与无损检测辐射类型教育周期实践部分有关的工业射线照相模拟器需求的主要因素。通过分析,确定了可虚拟实现的实践培训的最重要方面。在模拟无损检测辐射类型的技术过程中,在射线图像生成的数字孪生范围内,电离辐射的物理和物理化学过程、穿透辐射的衰减和吸收的数学模型的软件实施结果得到了展示。作为数字教育环境的一部分,以硬件和软件 VR 模拟器的形式实际实施了教学材料,以解决培训、再培训、人员认证准备和接纳专家在设施中从事辐射型无损检测工作的问题。对 VR 模拟器的物理和技术方面进行了分析、建模、算法和软件实施。介绍了利用数字技术创建学习环境的综合方法。考虑了主要组成部分、目标和目的。介绍了实践课程的结构和虚拟环境中的培训过程。在工业放射学 VR 模拟器中整合课程的培训计划获得批准的结果表明,学员的总实践时间增加了 40-55%,同时人均放射学实验室负荷减少了 25%以上。结论。经过开发和测试的软硬件解决方案以及科学研究的结果表明,使用 VR 环境的数字教育系统的应用和发展方向是可行的。建议的应用方法将通过使用软件和硬件解决方案降低对培训安全的要求,从而减少环境和生物医学风险。在软件工具和数学模型(包括人工智能方法)应用的基础上,实现测试任务生成和知识控制程序的自动化,将有助于缩短培训时间,并有助于进一步增加无损检测各种类型和方法的受训专家人数。在统一模块化方法、软件库和软硬件接口的基础上,随着软硬件解决方案(工业射线照相模拟器)功能的扩展和发展,虚拟模拟器简化了专家培训和知识控制过程的组织。数字虚拟环境(VR 环境)开发的实用价值体现在根据 GOST R 56542-2019 "无损检测。类型和方法分类"。
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引用次数: 0
Method for Forming Linear Scales for Assessing Learning Outcomes with Control of the Adequacy of Indicator Variables 形成线性量表以评估学习成果并控制指标变量适当性的方法
A. Maslak, A. Korobko
The purpose of the research is to construct a linear scale for assessing learning outcomes, and to assess the relevance of the indicator variables involved in the formation of the scale.Methods. An analysis of existing approaches to assessing competencies has shown that the most effective approach is the activity-based approach, which involves assessing competencies as a result of current, milestone and/or final control in a discipline or group of disciplines. For this, a scale is needed ‒ a measuring tool that allows you to assess the level of knowledge in a given competency. The quality of the measurement instrument was assessed within the framework of latent variable theory based on the Rasch model. We used the interactive environment “Measurement of Latent Variables, developed in the laboratory of objective measurements of Kuban State University, and the RUMM 2020 software, which is widely used in our country for processing student testing results.Results. For the universal competence Able to manage one’s time, build and implement a trajectory of self-development based on the principles of lifelong education, software and a pool of test tasks have been developed. Using latent variable theory, the validity of a linear scale for this competency was tested. Linear scale indicators have been identified that most adequately characterize the quality of knowledge level assessment, and indicators with the greatest and least sensitivity to the level of knowledge in this competency have been identified.Conclusion. The developed linear scale for assessing learning outcomes was used to measure the level of development of the universal competence UC-6 among students of Kuban State University. The results obtained are necessary for monitoring the formation of the UC-6 competence and for determining the factors influencing the formation of this competence.
研究的目的是构建评估学习成果的线性量表,并评估形成量表所涉及的指标变量的相关性。对现有能力评估方法的分析表明,最有效的方法是以活动为基础的方法,即把能力评估作为一门学科或一组学科的当前、里程碑和/或最终控制的结果。为此,需要一个量表--一种可以评估特定能力知识水平的测量工具。我们在基于 Rasch 模型的潜变量理论框架内对测量工具的质量进行了评估。我们使用了库班国立大学客观测量实验室开发的互动环境 "潜在变量测量 "和 RUMM 2020 软件,该软件在我国广泛用于处理学生测试结果。针对 "能够管理自己的时间,根据终身教育原则建立和实施自我发展轨迹 "这一通用能力,开发了软件和测试任务库。利用潜变量理论,对这一能力的线性量表的有效性进行了测试。已确定了最能充分表征知识水平评估质量的线性量表指标,并确定了对该能力知识水平最敏感和最不敏感的指标。所开发的学习成果评估线性量表用于衡量库班国立大学学生普遍能力 UC-6 的发展水平。所获得的结果对于监测 UC-6 能力的形成和确定影响该能力形成的因素非常必要。
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引用次数: 0
Method of Diagnosis of Glaucoma Based on Human Fundus Images 基于人体眼底图像的青光眼诊断方法
S. V. Komkova
The purpose of the research to develop a technique for detecting glaucoma, which is based on calculating the size ratio of the optical cup and optical disc and the "four quadrants" rule. Their use increases the accuracy of glaucoma detection in human retina images.Methods. A glaucoma detection technique is proposed that uses the ratio of the vertical diameter of the cup to the vertical diameter of the disc and the "four quadrants" rule as the two main parameters for the detection of glaucoma. The optic nerve disc (OD), the ocular cup (OCH) are segmented using the area extension method and the watershed method, and then combined to obtain the final results. Their union is performed using the logical operation OR. The resulting images are approximated using circular approximation, since its implementation is simple by calculating a single center and radius. For diagnostics, it was decided to use two parameters: the ratio of the cup and the disc (OCD) and the rule of "four quadrants". Their combined assessment makes it possible to increase the accuracy of glaucoma detection.Results: the study of the proposed technique was performed on retinal images obtained from 4 databases: HRF, DIARETDB1, DRIONS-DB, Messidor. The study showed that the proposed technique correctly identifies 75 retinal images as glaucoma out of 84 with a total sensitivity of 91.67%. Of the 163 normal images, 154 were correctly classified as normal with a specificity of 94.47%.Conclusion. The proposed method is simple and computationally efficient. It can be effectively used in computer diagnostics of glaucoma in the early stages of the disease.
研究的目的是开发一种检测青光眼的技术,该技术基于计算光学杯和光学盘的尺寸比以及 "四象限 "规则。它们的使用提高了人类视网膜图像中青光眼检测的准确性。本研究提出了一种青光眼检测技术,该技术以光杯垂直直径与光盘垂直直径之比以及 "四象限 "法则作为检测青光眼的两个主要参数。使用面积扩展法和分水岭法对视神经盘(OD)和眼杯(OCH)进行分割,然后将其合并以获得最终结果。它们的合并使用逻辑运算 OR 进行。生成的图像使用圆形近似法进行近似,因为只需计算一个中心和半径即可简单实现。在诊断方面,决定使用两个参数:杯和盘的比率(OCD)和 "四象限 "规则。结果:对从 4 个数据库中获得的视网膜图像进行了研究:HRF、DIARETDB1、DRIONS-DB 和 Messidor。研究表明,在 84 幅视网膜图像中,所提出的技术能正确识别出 75 幅为青光眼图像,总灵敏度为 91.67%。在 163 张正常图像中,154 张被正确分类为正常,特异性为 94.47%。所提出的方法简单,计算效率高。它可有效地用于青光眼早期阶段的计算机诊断。
{"title":"Method of Diagnosis of Glaucoma Based on Human Fundus Images","authors":"S. V. Komkova","doi":"10.21869/2223-1536-2023-13-4-99-114","DOIUrl":"https://doi.org/10.21869/2223-1536-2023-13-4-99-114","url":null,"abstract":"The purpose of the research to develop a technique for detecting glaucoma, which is based on calculating the size ratio of the optical cup and optical disc and the \"four quadrants\" rule. Their use increases the accuracy of glaucoma detection in human retina images.Methods. A glaucoma detection technique is proposed that uses the ratio of the vertical diameter of the cup to the vertical diameter of the disc and the \"four quadrants\" rule as the two main parameters for the detection of glaucoma. The optic nerve disc (OD), the ocular cup (OCH) are segmented using the area extension method and the watershed method, and then combined to obtain the final results. Their union is performed using the logical operation OR. The resulting images are approximated using circular approximation, since its implementation is simple by calculating a single center and radius. For diagnostics, it was decided to use two parameters: the ratio of the cup and the disc (OCD) and the rule of \"four quadrants\". Their combined assessment makes it possible to increase the accuracy of glaucoma detection.Results: the study of the proposed technique was performed on retinal images obtained from 4 databases: HRF, DIARETDB1, DRIONS-DB, Messidor. The study showed that the proposed technique correctly identifies 75 retinal images as glaucoma out of 84 with a total sensitivity of 91.67%. Of the 163 normal images, 154 were correctly classified as normal with a specificity of 94.47%.Conclusion. The proposed method is simple and computationally efficient. It can be effectively used in computer diagnostics of glaucoma in the early stages of the disease.","PeriodicalId":166124,"journal":{"name":"Proceedings of the Southwest State University. Series: IT Management, Computer Science, Computer Engineering. Medical Equipment Engineering","volume":"32 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139599892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Method and Algorithm for Implementing the Mandelbrot Set for Processing Complex Structured Images 用于处理复杂结构图像的曼德布罗特集实现方法和算法
R. A. Tomakova, I. M. Akhmadullin, N. G. Nefedov, E. I. Puzyrev, A. A. Malyshev
The purpose of research. In our life, fractals are ubiquitous, for example, in nature, there are a huge number of figures similar to themselves and built according to certain laws. Fractals are used in computer graphics, economics, radio engineering, physics and many other fields. The use of fractals in various fields of science can open up many new possibilities. Therefore, the development of a software product designed to visualize the Mandelbrot set is an urgent task. The purpose of the research is to develop a software product designed for processing complex structured images based on fractal methods and algorithms for visualizing the Mandelbrot set.Methods. The Java programming language was used to implement the software product in order to visualize the Mandelbrot set. The SQLite database was used as a local data store. Libraries were also used: JavaFX ‒ to create a user interface; SQLite JDBC 3.21.0 ‒ to work with the SQLite database; imgscalr ‒ to scale images; Apache Commons IO 2.6 to work with the file system; ControlsFX v8.40.14 ‒ to create a user interface.Results. The developed software product based on fractal methods makes it possible to significantly highlight the textural features of images, on the basis of which the clustering operation of selected objects of interest in images is performed in order to export them for further classification.Conclusion. During the implementation of the project, a software product for visualization of the Mandelbrot set was implemented, which can be used to model objects having a fractal shape, in relation to the processing of complexly structured images containing invisible hidden features of objects in the images.
研究目的在我们的生活中,分形无处不在,例如,在自然界中,存在着大量与自身相似并按照一定规律构建的图形。分形在计算机图形学、经济学、无线电工程学、物理学等许多领域都有应用。在各个科学领域使用分形可以带来许多新的可能性。因此,开发一种旨在将曼德勃罗特集可视化的软件产品是一项紧迫的任务。本研究的目的是开发一种基于分形方法和算法的软件产品,用于处理复杂的结构图像,使曼德布罗特集可视化。使用 Java 编程语言实现软件产品,以实现 Mandelbrot 集的可视化。SQLite 数据库用作本地数据存储。还使用了一些库:JavaFX - 用于创建用户界面;SQLite JDBC 3.21.0 - 用于连接 SQLite 数据库;imgscalr - 用于缩放图像;Apache Commons IO 2.6 - 用于连接文件系统;ControlsFX v8.40.14 - 用于创建用户界面。基于分形方法开发的软件产品能够显著突出图像的纹理特征,在此基础上对图像中选定的感兴趣对象进行聚类操作,以便导出图像进行进一步分类。在该项目的实施过程中,开发了一款用于曼德尔布罗特集可视化的软件产品,该产品可用于对具有分形形状的物体进行建模,用于处理结构复杂的图像,其中包含图像中不可见的隐藏物体特征。
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引用次数: 0
A Method for Assessing the Level of Nonspecific Protection of the Human Body by Indicators Characterizing the Processes of Adaptation 通过适应过程的特征指标评估人体非特异性保护水平的方法
S. N. Rodionova
The purpose of the research is to develop a method for assessing the level of nonspecific protection of the human body according to indicators characterizing the adaptation processes, the use of which in the decisive rules of forecasting and diagnosis of diseases ensures an improvement in the quality of decisions made.Methods. Numerous sources have a fairly detailed description of the protective mechanisms of the human body, implemented by non-specific and specific protection systems, which are closely related to such concepts as: adaptive potential, adaptive reserve, functional state and functional reserve. The paper investigates the use of indicators characterizing the adaptive potential and adaptive reserves for quantifying the nonspecific level of protection of the body from the effects of heterogeneous external factors. The methodology of synthesis of hybrid fuzzy decision rules is used as a basic mathematical apparatus.Results. The paper shows that to quantify the level of protection of the body, it is advisable to use an indicator of the activity of regulatory systems, adaptive potential, an indicator characterizing the immune-endocrine component of adaptation and an indicator characterizing the neuropsychic component of adaptation. For this system of indicators, a method has been developed to assess the level of protection based on basic indicators characterizing adaptation processes at the system-wide level, characterized by taking into account components characterizing various mechanisms for the formation of adaptive potential and adaptive reserve, taking into account the specifics of the data structure and ways of processing them for the best results in terms of quality and time of decisions. Fuzzy functions of the level of protection according to the selected system of indicators with an integral assessment of the level of protection of the body are obtained.Conclusion. The paper shows that in order to improve the quality of forecasting and diagnosis of socially significant and occupational diseases, it is advisable to use indicators of the level of protection of the body determined by adaptive mechanisms. It is established that the quality of decision–making using the proposed models increases by 10-15%, depending on the type of tasks being solved, compared with models that do not use indicators of the level of protection of the body.
研究的目的是根据适应过程的特征指标,开发一种评估人体非特异性保护水平的方法,在预测和诊断疾病的决定性规则中使用这种方法可以确保提高决策的质量。大量资料对人体的保护机制进行了相当详细的描述,这些机制由非特异性和特异性保护系统实施,与适应潜力、适应储备、功能状态和功能储备等概念密切相关。本文研究了如何利用表征适应潜能和适应储备的指标来量化人体免受异质外部因素影响的非特异性保护水平。混合模糊决策规则的合成方法被用作基本数学工具。论文表明,要量化人体保护水平,最好使用调节系统活动指标--适应潜能、表征适应的免疫-内分泌成分的指标和表征适应的神经心理成分的指标。针对这一指标体系,已开发出一种方法,根据表征全系统适应过程的基本指标来评估保护水平,其特点是考虑到表征适应潜力和适应储备形成的各种机制的组成部分,同时考虑到数据结构的具体情况和处理数据的方法,以便在决策的质量和时间方面取得最佳结果。根据选定的指标体系,获得了保护水平的模糊函数,并对人体保护水平进行了综合评估。本文表明,为了提高对社会重大疾病和职业病的预测和诊断质量,最好使用由适应机制确定的人体保护水平指标。与不使用人体保护水平指标的模型相比,使用所建议模型的决策质量可提高 10-15%,具体取决于所解决任务的类型。
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引用次数: 0
Technologies of Bioimpedance Spectroscopy in Decision Support Systems for the Diagnosis of Socially Significant Diseases 生物阻抗光谱技术在社会重大疾病诊断决策支持系统中的应用
O. V. Shatalova, N. Stadnichenko, M. A. Efremov, I. A. Bashmakova, A. V. Lyakh, A. V. Serebrovsky
The purpose of the research is to develop methods for the synthesis of hybrid classifiers to assess the risk of socially significant diseases using bioimpedance analysis.Methods. We developed a descriptor approach using impedance spectroscopy results, generating four amplitudephase-frequency responses from four quasi-orthogonal leads. They create the feature spaces necessary for our hybrid classifier in the diagnosis of pancreatic diseases, the autonomous intelligent agents of which are built on various paradigms: probabilistic neural networks, fuzzy logical inference, fully connected feedforward neural networks. We also presented a device structure for creating an informative feature space.Results. Experimental studies of the proposed methods and means of classifying medical rice were carried out on diagnostic tasks according to the classes "acute destructive pancreatitis" – "no acute destructive pancreatitis" and differential diagnosis tasks according to the classes "prostate cancer" ‒ "chronic pancreatitis". They showed that incorporating multi-frequency sensing into neural network-based classifiers allows the development of clinical decision support systems for disease diagnosis that are comparable in performance to existing clinical diagnostic methods. The results were confirmed in groups of male and female patients at different stages of cancer aged 25 to 80 years using a variety of diagnostic methods, including history, physical examination, assessment of comorbidities, laboratory tests, ultrasound, laparoscopy, intraoperative exploration and computed tomography.Conclusion. The use of bioimpedance spectroscopy and hybrid classifier models opens up new opportunities for accessible and objective diagnosis of pancreatic diseases, expanding the capabilities of intelligent medical decision support systems.
这项研究的目的是开发混合分类器的合成方法,以利用生物阻抗分析评估重大社会疾病的风险。我们利用阻抗光谱结果开发了一种描述符方法,从四个准正交导联生成四个幅相频率响应。它们为我们的胰腺疾病诊断混合分类器创建了必要的特征空间,该分类器的自主智能代理建立在各种范式之上:概率神经网络、模糊逻辑推理、全连接前馈神经网络。我们还提出了创建信息特征空间的设备结构。我们根据 "急性破坏性胰腺炎"-"无急性破坏性胰腺炎 "类别的诊断任务和 "前列腺癌"-"慢性胰腺炎 "类别的鉴别诊断任务,对所提出的医疗米分类方法和手段进行了实验研究。他们的研究表明,在基于神经网络的分类器中加入多频传感技术,可以开发出与现有临床诊断方法性能相当的疾病诊断临床决策支持系统。这些结果在一组 25 至 80 岁不同阶段的男性和女性癌症患者身上得到了证实,他们使用了多种诊断方法,包括病史、体格检查、合并症评估、实验室检查、超声波、腹腔镜检查、术中探查和计算机断层扫描。生物阻抗光谱和混合分类器模型的使用为胰腺疾病的客观诊断提供了新的机会,拓展了智能医疗决策支持系统的功能。
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引用次数: 0
Selection of a Neural Network Architecture for Implementation of Cognitive Functions of Network Software for Control of a Group of Interacting Small Space Vehicles 为控制一组相互作用的小型空间飞行器的网络软件实现认知功能选择神经网络架构
E. A. Shilenkov, S. N. Frolov, E. A. Titenko, S. Y. Miroshnichenko
The purpose of the research is to substantiate and select the architecture of a neural network for the possibility of implementing the cognitive functions of network software for controlling a grouping of interacting small spacecraft.Methods are based on the concepts of AI theory for managing the grouping of small spacecraft - the use of adaptive methods and tools that allow making decisions, similar to the mechanisms of human thinking. With regard to space communication systems with a heterogeneous structure, AI methods and technologies are aimed at the processes of predicting the state in communication channels between network nodes and automatic reconfiguration of the network of devices based on the learning processes of a neural network (NN).Results. In the learning and forecasting mode, it is necessary to use time series of parameters and coordinates of specific pairs of small spacecraft with non-zero line of sight. Especially for time series analysis, recurrent neural networks (RNN) are used, in particular, LSTM. The idea of RNN operation is to use as input data for the current forecast not only the state vectors of the SVs and their coordinates, but also the previous value of the communication quality, actual or predictive. The paper shows that the onboard computing power of a separate MSC does not allow performing forecasting and training on board. Therefore, a dedicated ground segment of forecasting and monitoring is required, which will collect a posteriori information, periodically train the cognitive model, use it to predict the quality of communication, and transmit the results to the network nodes to build data transmission routes.Conclusion. The analysis of modern solutions and the choice of neural network architecture for the implementation of the cognitive functions of the network software for controlling the grouping of interacting small spacecraft showed that the neural networks of the Transformer architecture, which are based on the mechanism of internal attention, most fully meet the requirements of the project. The Transformer architecture allows using the entirety of a priori data, has a high learning and forecasting speed.
研究的目的是证实和选择神经网络的结构,以实现网络软件的认知功能,从而控制相互作用的小型航天器的分组。关于具有异构结构的空间通信系统,人工智能方法和技术旨在预测网络节点之间通信通道的状态,并根据神经网络(NN)的学习过程自动重新配置设备网络。在学习和预测模式中,有必要使用非零视线小型航天器特定对的参数和坐标的时间序列。特别是在时间序列分析中,使用了递归神经网络(RNN),尤其是 LSTM。RNN 运行的思路是,不仅将 SV 的状态向量及其坐标作为当前预测的输入数据,而且还将通信质量的先前值(实际值或预测值)作为当前预测的输入数据。本文表明,独立 MSC 的机载计算能力无法在机上进行预测和训练。因此,需要一个专门的地面预测和监测段,负责收集后验信息、定期训练认知模型、利用认知模型预测通信质量,并将结果传输到网络节点,以建立数据传输路线。通过对现代解决方案的分析,以及为控制相互作用的小型航天器分组的网络软件的认知功能而选择的神经网络结构表明,基于内部注意力机制的 Transformer 结构的神经网络最能满足项目的要求。Transformer 架构允许使用全部先验数据,具有很高的学习和预测速度。
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引用次数: 0
Hybrid Neuro-Fuzzy Classifier for Monitoring the Effectiveness of Treatment of Diseases of the Respiratory System, Taking into Account Comorbidity 用于监测呼吸系统疾病治疗效果的混合神经模糊分类器,同时考虑到并发症
E. V. Petrunina, S. A. Filist, L. V. Shulga, V. V. Pesok, Hayder Ali H. Alawsi, A. V. Butusov
The purpose of research is to develop a hybrid neuro-fuzzy classifier for remote monitoring of the severity of community-acquired pneumonia, taking into account the risk of concomitant diseases.Methods. To assess the severity of community-acquired pneumonia and determine the effectiveness of its treatment plan, a hybrid neural network is included in the hybrid neuro-fuzzy classifier, which contains three macrolayers: PNNFNN-FNN*. The number of decisive blocks of the PNN macrolayer is equal to the number of segments allocated in the space of informative features, and the output of each PNN block produces risk and non-risk assessments of communityacquired pneumonia by severity clusters. Aggregation of decisions made over N segments of the space of informative features is carried out in the FNN layer, which has the structure of a fuzzy decision-making module. The aggregation of 2L PNN-FNN outputs occurs in the FNN* macrolayer. The same macrolayer takes into account the influence of comorbidity on the severity of community-acquired pneumonia.Results. The testing of a hybrid neuro-fuzzy classifier of the severity of community-acquired pneumonia was carried out on an experimental group of patients with community-acquired pneumonia with comorbidity in the form of coronary heart disease. Indicators of the quality of classification of the severity of pneumonia taking into account the risk of comorbid disease using the example of coronary heart disease showed that the aggregation of the classifier of the severity of community-acquired pneumonia and the classifier of the risk of comorbid disease in the form of a hybrid neuro-fuzzy classifier makes it possible to improve the quality of assessing the severity of community-acquired pneumonia by more than 10% for all quality indicators.Conclusion. A hybrid neuro-fuzzy classifier, built on different pattern recognition paradigms, makes it possible to identify clusters of disease severity and improve the quality indicators for classifying the severity of community-acquired pneumonia in the presence of comorbidity by an average of 12%.
研究目的是开发一种混合神经模糊分类器,用于远程监测社区获得性肺炎的严重程度,同时考虑并发症的风险。为了评估社区获得性肺炎的严重程度并确定其治疗方案的有效性,混合神经模糊分类器中包含了一个混合神经网络,它包含三个宏层:PNNFNN-FNN*。PNN 宏层的决定块数量与信息特征空间中分配的分段数量相等,每个 PNN 块的输出按严重程度分组产生社区获得性肺炎的风险和非风险评估。信息特征空间 N 个分段的决策汇总在 FNN 层进行,该层具有模糊决策模块的结构。2L PNN-FNN 输出的汇总在 FNN* 宏层中进行。同一宏层考虑了合并症对社区获得性肺炎严重程度的影响。混合神经-模糊分类器对社区获得性肺炎严重程度的测试是在一组患有冠心病的社区获得性肺炎患者身上进行的。以冠心病为例,考虑到并发症风险的肺炎严重程度分类质量指标表明,以混合神经模糊分类器的形式将社区获得性肺炎严重程度分类器和并发症风险分类器聚合在一起,可以将社区获得性肺炎严重程度评估质量的所有质量指标提高 10%以上。建立在不同模式识别范式基础上的混合神经模糊分类器能够识别疾病严重程度群,并将合并症情况下社区获得性肺炎严重程度的质量指标平均提高 12%。
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Proceedings of the Southwest State University. Series: IT Management, Computer Science, Computer Engineering. Medical Equipment Engineering
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