S. Kusuma^*, Dr. Jothi K. R

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1273-1289, 2022, DOI:10.32604/csse.2022.021741 - 10 November 2021

Abstract One of the severe health problems and the most common types of heart disease (HD) is Coronary heart disease (CHD). Due to the lack of a healthy lifestyle, HD would cause frequent mortality worldwide. If the heart attack occurs without any symptoms, it cannot be cured by an intelligent detection system. An effective diagnosis and detection of CHD should prevent human casualties. Moreover, intelligent systems employ clinical-based decision support approaches to assist physicians in providing another option for diagnosing and detecting HD. This paper aims to introduce a heart disease prediction model including phases like… More >

Qaisar Abbas^1,*, Mostafa E.A. Ibrahim^1,2, Shakir Khan¹, Abdul Rauf Baig¹

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1999-2007, 2022, DOI:10.32604/cmc.2022.022553 - 03 November 2021

Abstract Traffic accidents are caused by driver fatigue or distraction in many cases. To prevent accidents, several low-cost hypovigilance (hypo-V) systems were developed in the past based on a multimodal-hybrid (physiological and behavioral) feature set. Similarly in this paper, real-time driver inattention and fatigue (Hypo-Driver) detection system is proposed through multi-view cameras and biosignal sensors to extract hybrid features. The considered features are derived from non-intrusive sensors that are related to the changes in driving behavior and visual facial expressions. To get enhanced visual facial features in uncontrolled environment, three cameras are deployed on multiview points… More >

Wei Pei¹, Yan Li¹, Siuly Siuly^1,*, Peng Wen²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 889-905, 2022, DOI:10.32604/cmc.2022.021830 - 03 November 2021

Abstract Sleep stage classification plays a significant role in the accurate diagnosis and treatment of sleep-related diseases. This study aims to develop an efficient deep learning based scheme for correctly identifying sleep stages using multi-biological signals such as electroencephalography (EEG), electrocardiogram (ECG), electromyogram (EMG), and electrooculogram (EOG). Most of the prior studies in sleep stage classification focus on hand-crafted feature extraction methods. Traditional hand-crafted feature extraction methods choose features manually from raw data, which is tedious, and these features are limited in their ability to balance efficiency and accuracy. Moreover, most of the existing works on… More >

Jinho Bang¹, SongEe Park², Haemin Jeon^2,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1503-1519, 2022, DOI:10.32604/cmc.2022.020485 - 03 November 2021

Abstract Conductive cementitious composites are innovated materials that have improved electrical conductivity compared to general types of cement, and are expected to be used in a variety of future infrastructures with unique functionalities such as self-heating, electromagnetic shielding, and piezoelectricity. In the present study, machine learning methods that have been recently applied in various fields were proposed for the prediction of piezoelectric characteristics of carbon nanotubes (CNTs)-incorporated cement composites. Data on the resistivity change of CNTs/cement composites according to various water/binder ratios, loading types, and CNT content were considered as training values. These data were applied More >

Abdullah Ali Salamai^1,*, Ather Abdulrahman Ageeli¹, El-Sayed M. El-kenawy²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5091-5106, 2022, DOI:10.32604/cmc.2022.021268 - 11 October 2021

Abstract E-commerce refers to a system that allows individuals to purchase and sell things online. The primary goal of e-commerce is to offer customers the convenience of not going to a physical store to make a purchase. They will purchase the item online and have it delivered to their home within a few days. The goal of this research was to develop machine learning algorithms that might predict e-commerce platform sales. A case study has been designed in this paper based on a proposed continuous Stochastic Fractal Search (SFS) based on a Guided Whale Optimization Algorithm… More >

Kusum Yadav¹, Ali Alharbi¹, Anurag Jain^2,*, Rabie A. Ramadan¹

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3637-3652, 2022, DOI:10.32604/cmc.2022.020614 - 27 September 2021

Abstract Internet of things (IoT) field has emerged due to the rapid growth of artificial intelligence and communication technologies. The use of IoT technology in modern healthcare environments is convenient for doctors and patients as it can be used in real-time monitoring of patients, proper administration of patient information, and healthcare management. However, the usage of IoT in the healthcare domain will become a nightmare if patient information is not securely maintained while transferring over an insecure network or storing at the administrator end. In this manuscript, the authors have developed a secure IoT healthcare monitoring system… More >

Stefanie M. Croghan, Jody S.A. Khan, Prem Thomas Jacob, Hugh D. Flood, Subhasis K. Giri

Canadian Journal of Urology, Vol.28, No.3, pp. 10729-10732, 2021

Abstract Introduction: We aim to design a tool to assess the impact of recurrent urinary tract infection (rUTI) on quality of life (QoL) in adult women, given the notable absence of an established instrument for this purpose.
Materials and methods: Best practice guidelines in health-related survey design were reviewed. A literature review informed the creation of an interview guide. Following ethical approval, 10 female patients (23–38 years) with rUTI were invited to participate in phase 1 of questionnaire design; all agreed. Individual semi-structured interviews were conducted exploring the impact of rUTI on patients’ QoL. Interviews were repeated with… More >

Ross G. Everett, David K. Charles, Halle E. Foss, R. Corey O’Connor, Michael L. Guralnick

Canadian Journal of Urology, Vol.28, No.6, pp. 10920-10928, 2021

Abstract Introduction: Urinary Tract Infection (UTI) has been cited as the primary cause of morbidity in patients with a history of spinal cord injury (SCI). Despite the significance of recurrent UTI (rUTI) in this population, the causative physiologic and patient characteristics are not well described. We sought to assess associations between demographic, clinical, and urodynamic variables and rUTI.
Materials and methods: The records of 136 individuals with SCI who perform clean intermittent catheterization (CIC) were retrospectively reviewed. All had a video urodynamics study (VUDS) available for analysis. Individuals were divided into non-recurrent (< 3/year) or rUTI (≥ 3/year)… More >

Miguel Rodriguez-Homs¹, Brett Wiesen¹, Mona Rizeq², Colin Randau³, Granville L. Lloyd⁴

Canadian Journal of Urology, Vol.28, No.1, pp. 10565-10567, 2021

Abstract Prostate cancer is rarely metastatic to visceral organs, and even less commonly to the brain. Recent data suggests brain metastasis from prostatic adenocarcinoma occur in 0.16% of patients, and almost universally in the setting of very high-volume disease. We present a man with an abruptly symptomatic brain lesion that developed at a PSA value of 1.5 ng/mL with no other known metastatic disease and required emergent neurosurgical resection. The patient had been initially treated with radiotherapy for Grade Group 4 prostate cancer in 2005 with a long period of PSA suppression. More >

Asmaa E. E. Ali^*, Mofreh Mohamed Salem, Mahmoud Badway, Ali I. EL Desouky

Journal on Artificial Intelligence, Vol.3, No.3, pp. 81-96, 2021, DOI:10.32604/jai.2021.022433 - 25 January 2022

Abstract Breast cancer (BrC) is now the world’s leading cause of death for women. Early detection and effective treatment of this disease are the only rescues to reduce BrC mortality. The prediction of BrC diseases is very difficult because it is not an individual disease but a mixture of various diseases. Many researchers have used different techniques such as classification, Machine Learning (ML), and Deep Learning (DL) of the prediction of the breast tumor into Benign and Malignant. However, still there is a scope to introduce appropriate techniques for developing and implementing a more effective diagnosis… More >