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Fulltext Comparison of nested and ELISA based polymerase chain reaction assays for detecting Chlamydia trachomatis in pregnant women with preterm complications

Sulaiman S, Chong PP, Mokhtarudin R, Lye MS, Wan Hassan WH

Trop Biomed, 2014 Mar;31(1):36-45.
PMID: 24862043 MyJurnal

Identification of pregnant women infected with Chlamydia trachomatis is essential to allow early antibiotic treatment in order to prevent adverse pregnancy outcomes. In this study, two nucleic acid amplification tests (NAAT) namely nested PCR (BioSewoom, Korea) and Amplicor CT/NG (Roche Diagnostic, USA) were evaluated in terms of sensitivity and specificity for the detection of C. trachomatis DNA in pregnant women with preterm complications. A cross-sectional study was carried out in two public hospitals in Southern Selangor, Malaysia. Endocervical swabs obtained were subjected to DNA amplification using nested PCR (BioSewoom, Korea) and Amplicor CT/NG (Roche Diagnostic, USA). A total of 83 endocervical swabs obtained from pregnant women of less than 37 weeks gestation and presented with preterm complications were subjected to chlamydial DNA detection using both assays. The study shows that Amplicor CT/NG assay is more effective in the detection of C. trachomatis DNA from endocervical swabs compared to Biosewoom nested PCR kit. Agreement between the two assays were poor (kappa=0.094) with nested PCR showing a low sensitivity of 10.81% and a 97.83% specificity when compared to Amplicor CT/NG. The results obtained indicated that BioSewoom nested PCR was less sensitive than Amplicor CT/ NG for detecting C. trachomatis in endocervical specimens and that another more reliable test is required for confirmatory result.
A systematic review of security and privacy issues in the internet of medical things; the role of machine learning approaches

Hameed SS, Hassan WH, Abdul Latiff L, Ghabban F

PeerJ Comput Sci, 2021;7:e414.
PMID: 33834100 DOI: 10.7717/peerj-cs.414

Background: The Internet of Medical Things (IoMTs) is gradually replacing the traditional healthcare system. However, little attention has been paid to their security requirements in the development of the IoMT devices and systems. One of the main reasons can be the difficulty of tuning conventional security solutions to the IoMT system. Machine Learning (ML) has been successfully employed in the attack detection and mitigation process. Advanced ML technique can also be a promising approach to address the existing and anticipated IoMT security and privacy issues. However, because of the existing challenges of IoMT system, it is imperative to know how these techniques can be effectively utilized to meet the security and privacy requirements without affecting the IoMT systems quality, services, and device's lifespan.
Methodology: This article is devoted to perform a Systematic Literature Review (SLR) on the security and privacy issues of IoMT and their solutions by ML techniques. The recent research papers disseminated between 2010 and 2020 are selected from multiple databases and a standardized SLR method is conducted. A total of 153 papers were reviewed and a critical analysis was conducted on the selected papers. Furthermore, this review study attempts to highlight the limitation of the current methods and aims to find possible solutions to them. Thus, a detailed analysis was carried out on the selected papers through focusing on their methods, advantages, limitations, the utilized tools, and data.
Results: It was observed that ML techniques have been significantly deployed for device and network layer security. Most of the current studies improved traditional metrics while ignored performance complexity metrics in their evaluations. Their studies environments and utilized data barely represent IoMT system. Therefore, conventional ML techniques may fail if metrics such as resource complexity and power usage are not considered.
Fulltext Matrix metalloproteinase-9 and tissue inhibitors of metalloproteinases 1 and 2 as potential biomarkers for gestational hypertension

Ab Hamid J, Mohtarrudin N, Osman M, Andi Asri AA, Wan Hassan WH, Aziz R

Singapore Med J, 2012 Oct;53(10):681-3.
PMID: 23112021

Gestational hypertension (GH) is a common disorder during pregnancy that can progress to preeclampsia and cause various subsequent fatal complications. A cluster of enzymes, called matrix metalloproteinases (MMPs), and its specific inhibitors, tissue inhibitors of metalloproteinases (TIMPs), have been reported to be involved in the pathophysiology of GH. The purpose of this study was to examine circulating levels of MMP-9, TIMP-1 and TIMP-2 in pregnant women who had GH and those who were normotensive.
Fulltext HDG-select: A novel GUI based application for gene selection and classification in high dimensional datasets

Hameed SS, Hassan R, Hassan WH, Muhammadsharif FF, Latiff LA

PLoS One, 2021;16(1):e0246039.
PMID: 33507983 DOI: 10.1371/journal.pone.0246039

The selection and classification of genes is essential for the identification of related genes to a specific disease. Developing a user-friendly application with combined statistical rigor and machine learning functionality to help the biomedical researchers and end users is of great importance. In this work, a novel stand-alone application, which is based on graphical user interface (GUI), is developed to perform the full functionality of gene selection and classification in high dimensional datasets. The so-called HDG-select application is validated on eleven high dimensional datasets of the format CSV and GEO soft. The proposed tool uses the efficient algorithm of combined filter-GBPSO-SVM and it was made freely available to users. It was found that the proposed HDG-select outperformed other tools reported in literature and presented a competitive performance, accessibility, and functionality.
Fulltext IoMT amid COVID-19 pandemic: Application, architecture, technology, and security

Mohd Aman AH, Hassan WH, Sameen S, Attarbashi ZS, Alizadeh M, Latiff LA

J Netw Comput Appl, 2021 Jan 15;174:102886.
PMID: 34173428 DOI: 10.1016/j.jnca.2020.102886

In many countries, the Internet of Medical Things (IoMT) has been deployed in tandem with other strategies to curb the spread of COVID-19, improve the safety of front-line personnel, increase efficacy by lessening the severity of the disease on human lives, and decrease mortality rates. Significant inroads have been achieved in terms of applications and technology, as well as security which have also been magnified through the rapid and widespread adoption of IoMT across the globe. A number of on-going researches show the adoption of secure IoMT applications is possible by incorporating security measures with the technology. Furthermore, the development of new IoMT technologies merge with Artificial Intelligence, Big Data and Blockchain offers more viable solutions. Hence, this paper highlights the IoMT architecture, applications, technologies, and security developments that have been made with respect to IoMT in combating COVID-19. Additionally, this paper provides useful insights into specific IoMT architecture models, emerging IoMT applications, IoMT security measurements, and technology direction that apply to many IoMT systems within the medical environment to combat COVID-19.
Assessment of fluid status in CAPD patients using the body composition monitor

Cader RA, Gafor HA, Mohd R, Kong NC, Ibrahim S, Wan Hassan WH, et al.

J Clin Nurs, 2013 Mar;22(5-6):741-8.
PMID: 23039369 DOI: 10.1111/j.1365-2702.2012.04298.x

To assess the degree of overhydration in our peritoneal dialysis patients and to examine the factors contributing to overhydration.