Suzhe Wang^*, Xueying Zhang, Fenglian Li, Zelin Wu

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1177-1196, 2024, DOI:10.32604/cmc.2024.056016 - 15 October 2024

Abstract Early and timely diagnosis of stroke is critical for effective treatment, and the electroencephalogram (EEG) offers a low-cost, non-invasive solution. However, the shortage of high-quality patient EEG data often hampers the accuracy of diagnostic classification methods based on deep learning. To address this issue, our study designed a deep data amplification model named Progressive Conditional Generative Adversarial Network with Efficient Approximating Self Attention (PCGAN-EASA), which incrementally improves the quality of generated EEG features. This network can yield full-scale, fine-grained EEG features from the low-scale, coarse ones. Specially, to overcome the limitations of traditional generative models… More >

MIN SHEN^1,2, XIAOMAN XU^1,2, GUANGLING SUN¹, LIANGZHU WANG¹, TAO YING¹, HANG SU¹, WEI WANG¹, QINGHUA CAO^1,*, ZHEZHE SUN^1,*

BIOCELL, Vol.48, No.3, pp. 491-499, 2024, DOI:10.32604/biocell.2023.047640 - 15 March 2024

Abstract Objective: Circular RNAs (circRNAs) have been shown to involve in pathological processes of ischemic stroke (IS), including autophagy. This study was designed to explore the effect of circR-ZC3HC1 on neuronal autophagy in IS and the related mechanisms. Methods: Expression of circR-ZC3HC1 in blood samples of IS patients and healthy controls was detected. Hippocampal neurons were treated with oxygen and glucose deprivation (OGD) to establish IS in vitro model. The expression of LC3 and p62 and the number of autophagosomes were examined to evaluate the autophagy level of OGD induced neurons using western blotting and transmission electron… More >

Congjun Rao¹, Mengxi Li¹, Tingting Huang^2,*, Feiyu Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 699-724, 2024, DOI:10.32604/cmes.2023.044898 - 30 December 2023

Abstract Stroke is a chronic cerebrovascular disease that carries a high risk. Stroke risk assessment is of great significance in preventing, reversing and reducing the spread and the health hazards caused by stroke. Aiming to objectively predict and identify strokes, this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost (Logistic-AB) based on machine learning. First, the categorical boosting (CatBoost) method is used to perform feature selection for all features of stroke, and 8 main features are selected to form a new index evaluation system to predict the risk of stroke. Second, the borderline… More >

Zuo-Hua Li¹, Qing-Gui Wu^1,*, Jun Teng^1,*, Chao-Jun Chen^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 865-884, 2024, DOI:10.32604/cmes.2023.029927 - 22 September 2023

Abstract Collisions between a moving mass and an anti-collision device increase structural responses and threaten structural safety. An active mass damper (AMD) with stroke limitations is often used to avoid collisions. However, a stroke-limited AMD control system with a fixed limited area shortens the available AMD stroke and leads to significant control power. To solve this problem, the design approach with variable gain and limited area (VGLA) is proposed in this study. First, the boundary of variable-limited areas is calculated based on the real-time status of the moving mass. The variable gain (VG) expression at the More >

Mesfer Al Duhayyim^1,*, Sidra Abbas^2,*, Abdullah Al Hejaili³, Natalia Kryvinska⁴, Ahmad Almadhor⁵, Uzma Ghulam Mohammad⁶

Computer Systems Science and Engineering, Vol.47, No.1, pp. 413-429, 2023, DOI:10.32604/csse.2023.037127 - 26 May 2023

Abstract Stroke is a life-threatening disease usually due to blockage of blood or insufficient blood flow to the brain. It has a tremendous impact on every aspect of life since it is the leading global factor of disability and morbidity. Strokes can range from minor to severe (extensive). Thus, early stroke assessment and treatment can enhance survival rates. Manual prediction is extremely time and resource intensive. Automated prediction methods such as Modern Information and Communication Technologies (ICTs), particularly those in Machine Learning (ML) area, are crucial for the early diagnosis and prognosis of stroke. Therefore, this… More >

LUOJUN ZHENG, LUAN WENG, DIWEN SHOU^*

BIOCELL, Vol.47, No.6, pp. 1345-1352, 2023, DOI:10.32604/biocell.2023.028866 - 19 May 2023

Abstract Background: Ischemic stroke is characterized by permanent or transient obstruction of blood flow, leading to a growing risk factor and health burden. Tianmagouteng yin (TMG) is commonly used in Chinese medicine to treat cerebral ischemia. The aim of this study was to investigate the neuroprotective effects of TMG against ischemic stroke. Methods: Either permanent middle cerebral artery occlusion (pMCAO) or sham operation was performed on anesthetized Wistar male rats (n = 36). Results: Results demonstrated that TMG administration reduced the infarction volume and mitigated the neurobehavioral deficits. Hematoxylin and eosin (HE) staining and Prussian blue staining revealed More >

Azhar Tursynova¹, Batyrkhan Omarov^1,2, Natalya Tukenova^3,*, Indira Salgozha⁴, Onergul Khaaval³, Rinat Ramazanov⁵, Bagdat Ospanov⁵

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1431-1446, 2023, DOI:10.32604/cmc.2023.034400 - 06 February 2023

Abstract In the field of stroke imaging, deep learning (DL) has enormous untapped potential. When clinically significant symptoms of a cerebral stroke are detected, it is crucial to make an urgent diagnosis using available imaging techniques such as computed tomography (CT) scans. The purpose of this work is to classify brain CT images as normal, surviving ischemia or cerebral hemorrhage based on the convolutional neural network (CNN) model. In this study, we propose a computer-aided diagnostic system (CAD) for categorizing cerebral strokes using computed tomography images. Horizontal flip data magnification techniques were used to obtain more… More >

Shakunthala Masi^*, Helenprabha Kuttiappan

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 733-744, 2023, DOI:10.32604/iasc.2023.025919 - 29 September 2022

Abstract In medical science for envisaging human body’s phenomenal structure a major part has been driven by image processing techniques. Major objective of this work is to detect of cerebral atherosclerosis for image segmentation application. Detection of some abnormal structures in human body has become a difficult task to complete with some simple images. For expounding and distinguishing neural architecture of human brain in an effective manner, MRI (Magnetic Resonance Imaging) is one of the most suitable and significant technique. Here we work on detection of Cerebral Atherosclerosis from MRI images of patients. Cerebral Atherosclerosis is… More >

Shin Jin Kang¹, Soo Kyun Kim^2,*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2573-2588, 2023, DOI:10.32604/iasc.2023.029893 - 17 August 2022

Abstract In this paper, we propose an authentication method that use mouse and keystroke dynamics to enhance online privacy and security. The proposed method identifies personalized repeated user interface (UI) sequences by analyzing mouse and keyboard data. To this end, an Apriori algorithm based on the keystroke-level model (KLM) of the human–computer interface domain was used. The proposed system can detect repeated UI sequences based on KLM for authentication in the software. The effectiveness of the proposed method is verified through access testing using commercial applications that require intensive UI interactions. The results show using our More >

Moeiz Miraoui^1,2,*

Computer Systems Science and Engineering, Vol.44, No.1, pp. 677-692, 2023, DOI:10.32604/csse.2023.025799 - 01 June 2022

Abstract A cerebral vascular accident, known as common language stroke, is one of the main causes of mortality and remains the primary cause of acquired disabilities in adults. Those disabled people spend most of their time at home in their living rooms. In most cases, appliances of a living room (TV, light, cooler/heater, window blinds, etc.) are generally controlled by direct manipulation of a set of remote controls. Handling many remote controls can be disturbing and inappropriate for these people. In addition, in many cases these people could be alone at home and must open the… More >