Chinnapalli Likith Kumar^1,*, A. Vimala Juliet¹, Bandaru Ramakrishna², Shubhangi Chakraborty¹, Mazin Abed Mohammed³, Kalakanda Alfred Sunny⁴

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1369-1384, 2021, DOI:10.32604/cmc.2021.015116 - 05 February 2021

Abstract Microfluidic channels play a vital role in separation of analytes of interest such as bacteria and platelet cells, etc., in various biochemical diagnosis procedures including urinary tract infections (UTI) and bloodstream infections. This paper presents the multi physics computational model specifically designed to study the effects of design parameters of a microfluidics channel for the separation of Escherichia coli (E. coli) from various blood constituents including red blood cells (RBC) and platelets. A standard two inlet and a two outlet microchannel of length 805 m with a channel width of 40 m is simulated. The effect of… More >

Bilal Shoaib¹, Yasir Javed², Muhammad Adnan Khan^3,*, Fahad Ahmad⁴, Rizwan Majeed⁵, Muhammad Saqib Nawaz¹, Muhammad Adeel Ashraf⁶, Abid Iqbal², Muhammad Idrees⁷

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1413-1427, 2021, DOI:10.32604/cmc.2021.015099 - 05 February 2021

Abstract For the unforced dynamical non-linear statespace model, a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this article. The proposed algorithm lends itself towards the parallel implementation as in the FPGA systems. With the help of an ortho-normal triangularization method, which relies on numerically stable givens rotation, matrix inversion causes a computational burden, is reduced. Matrix computation possesses many excellent numerical properties such as singularity, symmetry, skew symmetry, and triangularity is achieved by using this algorithm. The proposed method is validated for the prediction of stationary and… More >

Kaustubh Arun Bhavsar¹, Ahed Abugabah², Jimmy Singla^1,*, Ahmad Ali AlZubi³, Ali Kashif Bashir⁴, Nikita⁵

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1997-2014, 2021, DOI:10.32604/cmc.2021.014943 - 05 February 2021

Abstract The unavailability of sufficient information for proper diagnosis, incomplete or miscommunication between patient and the clinician, or among the healthcare professionals, delay or incorrect diagnosis, the fatigue of clinician, or even the high diagnostic complexity in limited time can lead to diagnostic errors. Diagnostic errors have adverse effects on the treatment of a patient. Unnecessary treatments increase the medical bills and deteriorate the health of a patient. Such diagnostic errors that harm the patient in various ways could be minimized using machine learning. Machine learning algorithms could be used to diagnose various diseases with high… More >

Yasir Shahzad^1,*, Huma Javed¹, Haleem Farman², Jamil Ahmad², Bilal Jan³, Abdelmohsen A. Nassani⁴

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2463-2480, 2021, DOI:10.32604/cmc.2021.014904 - 05 February 2021

Abstract Smart healthcare integrates an advanced wave of information technology using smart devices to collect health-related medical science data. Such data usually exist in unstructured, noisy, incomplete, and heterogeneous forms. Annotating these limitations remains an open challenge in deep learning to classify health conditions. In this paper, a long short-term memory (LSTM) based health condition prediction framework is proposed to rectify imbalanced and noisy data and transform it into a useful form to predict accurate health conditions. The imbalanced and scarce data is normalized through coding to gain consistency for accurate results using synthetic minority oversampling… More >

Kavita Sahu¹, Fahad A. Alzahrani², R. K. Srivastava¹, Rajeev Kumar^3,4,*

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1471-1488, 2021, DOI:10.32604/cmc.2021.014868 - 05 February 2021

Abstract Maintaining software reliability is the key idea for conducting quality research. This can be done by having less complex applications. While developers and other experts have made significant efforts in this context, the level of reliability is not the same as it should be. Therefore, further research into the most detailed mechanisms for evaluating and increasing software reliability is essential. A significant aspect of growing the degree of reliable applications is the quantitative assessment of reliability. There are multiple statistical as well as soft computing methods available in literature for predicting reliability of software. However,… More >

Florin Valentin Leuciuc^1,2,*, Maria Daniela Craciun^1,2, Iulian Stefan Holubiac¹, Mazin Abed Mohammed³, Karrar Hameed Abdulkareem⁴, Gheorghe Pricop^1,2

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2601-2617, 2021, DOI:10.32604/cmc.2021.014863 - 05 February 2021

Abstract Identifying patterns, recognition systems, prediction methods, and detection methods is a major challenge in solving different medical issues. Few categories of devices for personal and professional assessment of body composition are available. Bioelectrical impedance analyzer is a simple, safe, affordable, mobile, non-invasive, and less expensive alternative device for body composition assessment. Identifying the body composition pattern of different groups with varying age and gender is a major challenge in defining an optimal level because of the body shape, body mass, energy requirements, physical fitness, health status, and metabolic profile. Thus, this research aims to identify… More >

Monagi H. Alkinani^1,*, E. A. Zanaty², Sherif M. Ibrahim³

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1577-1593, 2021, DOI:10.32604/cmc.2021.014803 - 05 February 2021

Abstract This paper presents a novel method utilizing wavelets with particle swarm optimization (PSO) for medical image compression. Our method utilizes PSO to overcome the wavelets discontinuity which occurs when compressing images using thresholding. It transfers images into subband details and approximations using a modified Haar wavelet (MHW), and then applies a threshold. PSO is applied for selecting a particle assigned to the threshold values for the subbands. Nine positions assigned to particles values are used to represent population. Every particle updates its position depending on the global best position (gbest) (for all details subband) and More >

Sally M. Elghamrawy¹, Aboul Ella Hassnien^2,*, Vaclav Snasel³

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2353-2371, 2021, DOI:10.32604/cmc.2021.014767 - 05 February 2021

Abstract Detecting COVID-19 cases as early as possible became a critical issue that must be addressed to avoid the pandemic’s additional spread and early provide the appropriate treatment to the affected patients. This study aimed to develop a COVID-19 diagnosis and prediction (AIMDP) model that could identify patients with COVID-19 and distinguish it from other viral pneumonia signs detected in chest computed tomography (CT) scans. The proposed system uses convolutional neural networks (CNNs) as a deep learning technology to process hundreds of CT chest scan images and speeds up COVID-19 case prediction to facilitate its containment.… More >

Saleh Albahli¹, Tahira Nazir^2,*, Aun Irtaza², Ali Javed³

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1333-1351, 2021, DOI:10.32604/cmc.2021.014691 - 05 February 2021

Abstract Diabetes is a metabolic disorder that results in a retinal complication called diabetic retinopathy (DR) which is one of the four main reasons for sightlessness all over the globe. DR usually has no clear symptoms before the onset, thus making disease identification a challenging task. The healthcare industry may face unfavorable consequences if the gap in identifying DR is not filled with effective automation. Thus, our objective is to develop an automatic and cost-effective method for classifying DR samples. In this work, we present a custom Faster-RCNN technique for the recognition and classification of DR… More >

Muhammad Waqas Nadeem^1,2, Hock Guan Goh^1,*, Muhammad Adnan Khan³, Muzammil Hussain⁴, Muhammad Faheem Mushtaq⁵, Vasaki a/p Ponnusamy¹

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2481-2496, 2021, DOI:10.32604/cmc.2021.014649 - 05 February 2021

Abstract The contemporary evolution in healthcare technologies plays a considerable and significant role to improve medical services and save human lives. Heart disease or cardiovascular disease is the most fatal and complex disease which it is hardly to be detected through our naked eyes, as numerous people have been suffering from this disease globally. Heart attacks occur when the ranges of vital signs such as blood pressure, pulse rate, and body temperature exceed their normal values. The efficient diagnosis of heart diseases could play a substantial role in the field of cardiology, while diagnostic time could… More >