Syed Sajid Ullah¹, Saddam Hussain¹, Abdu Gumaei^2,3,*, Mohsin S. Alhilal⁴, Bader Fahad Alkhamees⁴, Mueen Uddin⁵, Mabrook Al-Rakhami²

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 233-249, 2022, DOI:10.32604/cmc.2022.017971 - 07 September 2021

Abstract Nowadays, healthcare has become an important area for the Internet of Things (IoT) to automate healthcare facilities to share and use patient data anytime and anywhere with Internet services. At present, the host-based Internet paradigm is used for sharing and accessing healthcare-related data. However, due to the location-dependent nature, it suffers from latency, mobility, and security. For this purpose, Named Data Networking (NDN) has been recommended as the future Internet paradigm to cover the shortcomings of the traditional host-based Internet paradigm. Unfortunately, the novel breed lacks a secure framework for healthcare. This article constructs an More >

Cord J. Peters¹, Clesson E. Turner², Gregory T. Chesnut^3,4, Veda N. Giri^5,6, Leonard G. Gomella⁵, Craig D. Shriver^3,7, Albert Dobi³

Canadian Journal of Urology, Vol.28, No.3, pp. 10659-10667, 2021

Abstract Introduction: The objective of our review is to summarize the 2019 Philadelphia Prostate Cancer Genetic Consensus recommendations and discuss their implications to the US Military Health System.
Materials and methods: Literature review.
Results: Our fighting force and retired service members will significantly benefit from the Philadelphia Prostate Cancer Genetic Consensus recommendations. Moreover, the experience of the equal access US Military Health System may help advancing genetic testing for cancer at national levels.
Conclusions: Priorities recommended by the 2019 Consensus for more research on genetic predisposition to prostate cancer in racially diverse populations is a promising step. The US Military More >

Emily Nguyen¹, Michelle Minkovich¹, Olusegun Famure¹, Yanhong Li¹, Anand Ghanekar^1,2, Markus Selzner^1,2,*, S. Joseph Kim^1,3,*, Jason Y. Lee^1,4

Canadian Journal of Urology, Vol.28, No.5, pp. 10848-10857, 2021

Abstract Introduction: Following kidney transplantation, lymphoceles can impact patient and graft outcomes, while resulting in significant hospital resource utilization. We aimed to characterize the incidence, risk factors, outcomes, and clinical management of lymphoceles among kidney transplant recipients and review impact on health system utilization at a high-volume center.
Materials and methods: We conducted a single-center, observational cohort study on adults transplanted between January 1, 2005 and December 31, 2017. Incidence, risk factors, and clinical outcomes were assessed using the Kaplan-Meier product-limit method, multivariable logistic regression model, and Cox proportional hazards model, respectively.
Results: Lymphoceles developed in 72 of 1881… More >

Michael E. Rezaee¹, Annah J. Vollstedt¹, Tammer Yamany², Manoj Monga^3,4, Amy Krambeck^4,5, Ojas Shah^4,6, Roger L. Sur^3,4, Anna M. Zampini^4,7, Kymora B. Scotland^4,8, Ben H. Chew^4,8, Brian H. Eisner^2,4, Vernon M. Pais Jr^1,4

Canadian Journal of Urology, Vol.28, No.1, pp. 10516-10521, 2021

Abstract Introduction: To assess the relationship between pain after ureteral stent removal and patient and procedural factors.
Materials and methods: A validated survey designed to assess the relationship between quality of life and treatment decisions in kidney stone disease was randomly distributed to patients with a history of a ureteral stent in seven medical centers across North America participating in an endourology research collaborative between July 2016 and June 2018. The primary outcome was increased pain after ureteral stent removal. Statistical analyses were performed using Chi-square and multiple logistic regression.
Results: A total of 327 surveys were analyzed. Twenty… More >

Ali Abdulameer Aldujaili¹, Mohammed Dauwed², Ahmed Meri^3,*

Journal on Internet of Things, Vol.3, No.4, pp. 131-137, 2021, DOI:10.32604/jiot.2021.015994 - 30 December 2021

Abstract Parents concerns for their children who has a critical health conditions may limit the children movements and live to engage with others peers anytime and anywhere. Thus, in this study aims to propose a framework to help the children who has critical disease to have more activity and engagement with other peers. Additionally, reducing their parents’ concerns by providing monitoring and tracking system to their parents for their children health conditions. However, this study proposed a framework include tracking and monitoring wearable (TMW) device and decision system to alert healthcare providers and parents for any More >

Faisal Jamil¹, Faiza Qayyum¹, Soha Alhelaly², Farjeel Javed³, Ammar Muthanna^4,5,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2513-2530, 2021, DOI:10.32604/cmc.2021.018809 - 21 July 2021

Abstract Nowadays, the blockchain, Internet of Things, and artificial intelligence technology revolutionize the traditional way of data mining with the enhanced data preprocessing, and analytics approaches, including improved service platforms. Nevertheless, one of the main challenges is designing a combined approach that provides the analytics functionality for diverse data and sustains IoT applications with robust and modular blockchain-enabled services in a diverse environment. Improved data analytics model not only provides support insights in IoT data but also fosters process productivity. Designing a robust IoT-based secure analytic model is challenging for several purposes, such as data from… More >

C. Rajinikanth¹, P. Selvaraj², Mohamed Yacin Sikkandar³, T. Jayasankar⁴, Seifedine Kadry⁵, Yunyoung Nam^6,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2013-2029, 2021, DOI:10.32604/cmc.2021.018719 - 21 July 2021

Abstract Internet of Things (IoT) has become a major technological development which offers smart infrastructure for the cloud-edge services by the interconnection of physical devices and virtual things among mobile applications and embedded devices. The e-healthcare application solely depends on the IoT and cloud computing environment, has provided several characteristics and applications. Prior research works reported that the energy consumption for transmission process is significantly higher compared to sensing and processing, which led to quick exhaustion of energy. In this view, this paper introduces a new energy efficient cluster enabled clinical decision support system (EEC-CDSS) for… More >

Adil Hussain Seh¹, Jehad F. Al-Amri², Ahmad F. Subahi³, Alka Agrawal¹, Rajeev Kumar^4,*, Raees Ahmad Khan¹

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 697-712, 2021, DOI:10.32604/iasc.2021.018048 - 01 July 2021

Abstract The Adoption of Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), cloud services, web-based software systems, and other wireless sensor devices in the healthcare infrastructure have led to phenomenal improvements and benefits in the healthcare sector. Digital healthcare has ensured early diagnosis of the diseases, greater accessibility, and mass outreach in terms of treatment. Despite this unprecedented success, the privacy and confidentiality of the healthcare data have become a major concern for all the stakeholders. Data breach reports reveal that the healthcare data industry is one of the key targets of cyber invaders.… More >

Y. Sreeraman^*, S. Lakshmana Pandian

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 539-557, 2021, DOI:10.32604/iasc.2021.017256 - 16 June 2021

Abstract Causal relationships in a data play vital role in decision making. Identification of causal association in data is one of the important areas of research in data analytics. Simple correlations between data variables reveal the degree of linear relationship. Partial correlation explains the association between two variables within the control of other related variables. Partial association test explains the causality in data. In this paper a couple of causal relationship discovery strategies are proposed using the design of partial association tree that makes use of partial association test among variables. These decision trees are different… More >

Mehedi Masud^*, Mohammad Dahman Alshehri, Roobaea Alroobaea, Mohammad Shorfuzzaman

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 1-13, 2021, DOI:10.32604/iasc.2021.016800 - 12 May 2021

Abstract In 2020, the world faced an unprecedented pandemic outbreak of coronavirus disease (COVID-19), which causes severe threats to patients suffering from diabetes, kidney problems, and heart problems. A rapid testing mechanism is a primary obstacle to controlling the spread of COVID-19. Current tests focus on the reverse transcription-polymerase chain reaction (RT-PCR). The PCR test takes around 4–6 h to identify COVID-19 patients. Various research has recommended AI-based models leveraging machine learning, deep learning, and neural networks to classify COVID-19 and non-COVID patients from chest X-ray and computerized tomography (CT) scan images. However, no model can… More >