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

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 proposed work, the iterative weighted… More >

Fuat Turk^1,*, Murat Luy², Necaattin Barışçı³, Fikret Yalçınkaya⁴

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 349-363, 2022, DOI:10.32604/iasc.2022.023710

Abstract Cases of kidney cancer have shown a rapid increase in recent years. Advanced technology has allowed bettering the existing treatment methods. Research on the subject is still continuing. Medical segmentation is also of increasing importance. In particular, deep learning-based studies are of great importance for accurate segmentation. Tumor detection is a relatively difficult procedure for soft tissue organs such as kidneys and the prostate. Kidney tumors, specifically, are a type of cancer with a higher incidence in older people. As age progresses, the importance of having diagnostic tests increases. In some cases, patients with kidney tumors may not show any… More >

CLAIRE ELIZABETH HILLS, ELEFTHERIOS SIAMANTOURAS, PAUL EDWARD SQUIRES^*

BIOCELL, Vol.46, No.4, pp. 937-940, 2022, DOI:10.32604/biocell.2022.018414

Abstract Changes in cell-cell and cell-substrate adhesion markers are increasingly used to characterize disease onset and progression. However, these relationships depend on both the biochemical and molecular association between cells and between cells and their extracellular matrix, as well as the biophysical and mechanical properties orchestrated by cytoskeletal, membrane and matrix components. To fully appreciate the role of cell adhesion when determining normal physiology and the impact of disease on cellular function, it is important to consider both biochemical and biophysical attributes of the system being investigated. In this short viewpoint we reflect on our experiences assessing cell-cell and/or cell-matrix interactions… More >

R. H. Aswathy^1,*, P. Suresh¹, Mohamed Yacin Sikkandar², S. Abdel-Khalek³, Hesham Alhumyani⁴, Rashid A. Saeed⁴, Romany F. Mansour⁵

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2097-2111, 2022, DOI:10.32604/cmc.2022.019790

Abstract In recent times, Internet of Things (IoT) and Cloud Computing (CC) paradigms are commonly employed in different healthcare applications. IoT gadgets generate huge volumes of patient data in healthcare domain, which can be examined on cloud over the available storage and computation resources in mobile gadgets. Chronic Kidney Disease (CKD) is one of the deadliest diseases that has high mortality rate across the globe. The current research work presents a novel IoT and cloud-based CKD diagnosis model called Flower Pollination Algorithm (FPA)-based Deep Neural Network (DNN) model abbreviated as FPA-DNN. The steps involved in the presented FPA-DNN model are data… More >

Vinothini Arumugam^*, S. Baghavathi Priya

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 947-959, 2022, DOI:10.32604/iasc.2022.018654

Abstract Nowadays, Chronic Kidney Disease (CKD) is one of the vigorous public health diseases. Hence, early detection of the disease may reduce the severity of its consequences. Besides, medical databases of any disease diagnosis may be collected from the blood test, urine test, and patient history. Nevertheless, medical information retrieved from various sources is diverse. Therefore, it is unadaptable to evaluate numerical and nominal features using the same feature selection algorithm, which may lead to fallacious analysis. Applying machine learning techniques over the medical database is a common way to help feature identification for CKD prediction. In this paper, a novel… More >

A. Shahzad¹, W. A. Khan^2,*, R. Gul¹, B. Dayyan¹, M. Zubair¹

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3877-3893, 2021, DOI:10.32604/cmc.2021.012524

Abstract In this work, a steady, incompressible Williamson fluid model is investigated in a porous wavy channel. This situation arises in the reabsorption of useful substances from the glomerular filtrate in the kidney. After 80% reabsorption, urine is left, which behaves like a thinning fluid. The laws of conservation of mass and momentum are used to model the physical problem. The analytical solution of the problem in terms of stream function is obtained by a regular perturbation expansion method. The asymptotic integration method for small wave amplitudes and the RK-Fehlberg method for pressure distribution has been used inside the channel. It… More >

TING LI^1,#, XINHUI SUN^2,#, NANNAN LI¹, HONGMIN GUO^2,*

BIOCELL, Vol.45, No.4, pp. 985-994, 2021, DOI:10.32604/biocell.2021.012371

Abstract Fibroblast growth factors (FGFs) play pivotal roles in cell migration and proliferation. However, the identity of the FGF that plays a dominant role in kidney cell proliferation remains unclear. Therefore, in this study, we investigated the dominant FGF among all FGFs. To this end, RNA-sequencing, qRT-PCR, western blotting, and ChIP assays were performed. FGF9 showed the highest expression among all FGFs, and its overexpression significantly promoted proliferation in the mouse kidney cell line C57BL/6 and increased JNK and AKT phosphorylation levels. Further, RNA-seq analysis identified 365 upregulated and 276 downregulated genes in FGF9-overexpressed cells. These differentially expressed genes were classified… More >

Hamid A. Jalab^1,*, Rabha W. Ibrahim², Ali M. Hasan³, Faten Khalid Karim⁴, Ala’a R. Al-Shamasneh¹, Dumitru Baleanu^5,6,7

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1467-1483, 2021, DOI:10.32604/cmc.2021.016047

Abstract The enhancement of medical images is a challenging research task due to the unforeseeable variation in the quality of the captured images. The captured images may present with low contrast and low visibility, which might influence the accuracy of the diagnosis process. To overcome this problem, this paper presents a new fractional integral entropy (FITE) that estimates the unforeseeable probabilities of image pixels, posing as the main contribution of the paper. The proposed model dynamically enhances the image based on the image contents. The main advantage of FITE lies in its capability to enhance the low contrast intensities through pixels’… More >

MENGDAN WU¹, MENGYAO SUN¹, QINHUAI LAI¹, YIN LU¹, YUYIN FU¹, YUJIA PENG¹, WEIRONG LAI¹, LISHI ZENG¹, SHENGYAN ZHAO¹, YUYAN LI¹, ZHIXIONG ZHANG¹, XIAOFENG CHEN¹, FAN QIAO¹, YIWEN ZHANG^1,*, SHIJIE ZHOU^1,2,*, LANTU GOU¹, JINLIANG YANG^1,2

BIOCELL, Vol.45, No.3, pp. 589-597, 2021, DOI:10.32604/biocell.2021.013882

Abstract The chemokine ligand 13-chemokine receptor 5 (CXCL13-CXCR5) axis has been characterized as a critical tumor-promoting signaling pathway in the tumor microenvironment (TME) in multiple types of solid tumors. In this study, we analyzed the expression profile of CXCL13 in kidney clear cell carcinoma (KIRC) and its correlation with tumor-infiltrating immune cells (TIICs). A monoclonal antibody against CXCL13 with high affinity and purity was generated in our lab for western blot and immunohistochemistry (IHC). Bioinformatic analysis was performed based on bulk-seq data from the Cancer Genome Atlas (TCGA)-KIRC and single-cell RNA-seq data from scRNASeqDB and PanglaoDB. Results showed that high CXCL13… More >

Hamid A. Jalab¹, Ala’a R. Al-Shamasneh¹, Hadil Shaiba², Rabha W. Ibrahim^3,4,*, Dumitru Baleanu^5,6,7

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2061-2075, 2021, DOI:10.32604/cmc.2021.015170

Abstract Recently, many rapid developments in digital medical imaging have made further contributions to health care systems. The segmentation of regions of interest in medical images plays a vital role in assisting doctors with their medical diagnoses. Many factors like image contrast and quality affect the result of image segmentation. Due to that, image contrast remains a challenging problem for image segmentation. This study presents a new image enhancement model based on fractional Rényi entropy for the segmentation of kidney MRI scans. The proposed work consists of two stages: enhancement by fractional Rényi entropy, and MRI Kidney deep segmentation. The proposed… More >