R. Muthaiyan^1,*, M. Malleswaran²

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 891-907, 2022, DOI:10.32604/iasc.2022.024635 - 08 February 2022

Abstract Brain tumours are composed of cells where the growth is unrestrained. Though the incidence rate is lower, it is a serious threatening disease to human lives. For effective treatment, an accurate and quick method to classify Magnetic Resonance Imaging (MRI) is required. To identify the meaningful patterns and to interpret images, pattern recognition algorithms are developed. In this work, an extension of Shearlet transform named Bendlets is employed to interpret MRI images and decision making is done by ensemble learning using k-Nearest Neighbor (kNN), Naive Bayesian and Support Vector Machine (SVM) classifiers. The Bendlet and Ensemble More >

S. Jacophine Susmi^*

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1139-1152, 2022, DOI:10.32604/iasc.2022.023865 - 08 February 2022

Abstract The classification of cancer subtypes is substantial for the diagnosis and treatment of cancer. However, the gene expression data used for cancer subtype classification are high dimensional in nature and small in sample size. In this paper, an efficient dimensionality reduction with optimized long short term memory, algorithm (OLSTM) is used for gene expression data classification. The main three stages of the proposed method are explicitly pre-processing, dimensional reduction, and gene expression data classification. In the pre-processing method, the missing values and redundant values are removed for high-quality data. Following, the dimensional reduction is done More >

Zi Ye¹, Yogan Jaya Kumar², Goh Ong Sing², Fengyan Song³, Xianda Ni^4,*

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1197-1215, 2022, DOI:10.32604/iasc.2022.023555 - 08 February 2022

Abstract The determination of the probe viewpoint forms an essential step in automatic echocardiographic image analysis. However, classifying echocardiograms at the video level is complicated, and previous observations concluded that the most significant challenge lies in distinguishing among the various adjacent views. To this end, we propose an ECHO-Attention architecture consisting of two parts. We first design an ECHO-ACTION block, which efficiently encodes Spatio-temporal features, channel-wise features, and motion features. Then, we can insert this block into existing ResNet architectures, combined with a self-attention module to ensure its task-related focus, to form an effective ECHO-Attention network. More >

K. Poongodi^1,*, A. Sabari²

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 939-953, 2022, DOI:10.32604/iasc.2022.023038 - 08 February 2022

Abstract The microarray gene expression data has a large number of genes with different expression levels. Analyzing and classifying datasets with entire gene space is quite difficult because there are only a few genes that are informative. The identification of bio-marker genes is significant because it improves the diagnosis of cancer disease and personalized medicine is suggested accordingly. Initially, the parallelized minimum redundancy and maximum relevance ensemble (mRMRe) is employed to select top m informative genes. The selected genes are then fed into the Genetic Algorithm (GA) that selects the optimal set of genes heuristically, which More >

Mohd Anul Haq^*

Computer Systems Science and Engineering, Vol.42, No.3, pp. 1031-1046, 2022, DOI:10.32604/csse.2022.023221 - 08 February 2022

Abstract To adopt sustainable crop practices in changing climate, understanding the climatic parameters and water requirements with vegetation is crucial on a spatiotemporal scale. The Planetscope (PS) constellation of more than 130 nanosatellites from Planet Labs revolutionize the high-resolution vegetation assessment. PS-derived Normalized Difference Vegetation Index (NDVI) maps are one of the highest resolution data that can transform agricultural practices and management on a large scale. High-resolution PS nanosatellite data was utilized in the current study to monitor agriculture’s spatiotemporal assessment for the Al-Qassim region, Kingdom of Saudi Arabia (KSA). The time series of NDVI was… More >

Anisha Rebinth^1,*, S. Mohan Kumar²

Computer Systems Science and Engineering, Vol.42, No.3, pp. 867-880, 2022, DOI:10.32604/csse.2022.022955 - 08 February 2022

Abstract In this study, a Discriminator Model for Glaucoma Diagnosis (DMGD) using soft computing techniques is presented. As the biomedical images such as fundus images are often acquired in high resolution, the Region of Interest (ROI) for glaucoma diagnosis must be selected at first to reduce the complexity of any system. The DMGD system uses a series of pre-processing; initial cropping by the green channel’s intensity, Spatially Weighted Fuzzy C Means (SWFCM), blood vessel detection and removal by Gaussian Derivative Filters (GDF) and inpainting algorithms. Once the ROI has been selected, the numerical features such as More >

Majdy Mohamed Eltayeb Eltahir^1,*, Tarig Mohammed Ahmed^2,3

Computer Systems Science and Engineering, Vol.42, No.3, pp. 1257-1272, 2022, DOI:10.32604/csse.2022.022942 - 08 February 2022

Abstract In developed and developing countries, breast cancer is one of the leading forms of cancer affecting women alike. As a consequence of growing life expectancy, increasing urbanization and embracing Western lifestyles, the high prevalence of this cancer is noted in the developed world. This paper aims to develop a novel model that diagnoses Breast Cancer by using heterogeneous datasets. The model can work as a strong decision support system to help doctors to make the right decision in diagnosing breast cancer patients. The proposed model is based on three datasets to develop three sub-models. Each More >

S. Karthiga^*, A. M. Abirami

Computer Systems Science and Engineering, Vol.42, No.3, pp. 851-866, 2022, DOI:10.32604/csse.2022.021935 - 08 February 2022

Abstract Much attention has been given to the Internet of Things (IoT) by citizens, industries, governments, and universities for applications like smart buildings, environmental monitoring, health care and so on. With IoT, network connectivity is facilitated between smart devices from anyplace and anytime. IoT-based health monitoring systems are gaining popularity and acceptance for continuous monitoring and detect health abnormalities from the data collected. Electrocardiographic (ECG) signals are widely used for heart diseases detection. A novel method has been proposed in this work for ECG monitoring using IoT techniques. In this work, a two-stage approach is employed.… More >

S. Prakash^1,*, P. Vishnu Raja², A. Baseera³, D. Mansoor Hussain⁴, V. R. Balaji⁵, K. Venkatachalam⁶

Computer Systems Science and Engineering, Vol.42, No.3, pp. 1273-1287, 2022, DOI:10.32604/csse.2022.021784 - 08 February 2022

Abstract Urban living in large modern cities exerts considerable adverse effects on health and thus increases the risk of contracting several chronic kidney diseases (CKD). The prediction of CKDs has become a major task in urbanized countries. The primary objective of this work is to introduce and develop predictive analytics for predicting CKDs. However, prediction of huge samples is becoming increasingly difficult. Meanwhile, MapReduce provides a feasible framework for programming predictive algorithms with map and reduce functions. The relatively simple programming interface helps solve problems in the scalability and efficiency of predictive learning algorithms. In the… More >

IGOR A. KHLUSOV^1,*, LARISA S. LITVINOVA^2,*, KRISTINA A. YUROVA², MARINA Y. KHLUSOVA³

BIOCELL, Vol.46, No.6, pp. 1365-1373, 2022, DOI:10.32604/biocell.2022.018917 - 07 February 2022

Abstract Stem cell microterritories (niches), as a specialized part of the extracellular matrix (ECM), are considered an important target and tool for the development of new materials, medical implants, and devices. However, tissue bioengineering products that have stem cell niches of known size on the surface or in the bulk structure of artificial materials are practically unknown. This brief review attempts to draw attention to the problematic aspects of niches as specific parts of the ECM, such as their hierarchy and size for mesenchymal stromal/stem cells (MSCs). These parameters arise directly from numerous definitions of stem More >