Displaying all 19 publications

Abstract:
Sort:
  1. Rosli R, Abdul Kadir MR, Kamarul T
    Proc Inst Mech Eng H, 2014 Apr;228(4):342-9.
    PMID: 24622982 DOI: 10.1177/0954411914527074
    Anterior corpectomy and reconstruction using a plate with locking screws are standard procedures for the treatment of cervical spondylotic myelopathy. Although adding more screws to the construct will normally result in improved fixation stability, several issues need to be considered. Past reports have suggested that increasing the number of screws can result in the increase in spinal rigidity, decreased spine mobility, loss of bone and, possibly, screw loosening. In order to overcome this, options to have constrained, semi-constrained or hybrid screw and plate systems were later introduced. The purpose of this study is to compare the stability achieved by four and two screws using different plate systems after one-level corpectomy with placement of cage. A three-dimensional finite-element model of an intact C1-C7 segment was developed from computer tomography data sets, including the cortical bone, soft tissue and simulated corpectomy fusion at C4-C5. A spinal cage and an anterior cervical plate with different numbers of screws and plate systems were constructed to a fit one-level corpectomy of C5. Moment load of 1.0 N m was applied to the superior surface of C1, with C7 was fixed in all degrees of freedom. The kinematic stability of a two-screw plate was found to be statistically equivalent to a four-screw plate for one-level corpectomy. Thus, it can be a better option of fusion and infers comparable stability after one-level anterior cervical corpectomy, instead of a four-screw plate.
  2. Mohammed R, Goh KL, Wong NW
    Med J Malaysia, 1996 Mar;51(1):99-102.
    PMID: 10967987
    Primary biliary cirrhosis is an uncommon disease amongst Malaysians. Over a 12-year period, between 1979 and 1991, only seven patients with clinical, biochemical and histologic evidence of primary biliary cirrhosis were identified in University Hospital Kuala Lumpur. All were Chinese females between the ages of 30 to 55 years. The presenting complaint was pruritus in 5 patients. All except one patient was jaundiced when the diagnosis was made. These patients were followed up from 1 to 11 years. Three deaths were reported, one from massive hemetemesis and two from liver failure.
  3. Tata MD, Kwan KC, Abdul-Razak MR, Paramalingam S, Yeen WC
    Ann Thorac Surg, 2009 May;87(5):1613-4.
    PMID: 19379926 DOI: 10.1016/j.athoracsur.2008.10.019
    A 39-year-old Indian man presented with necrotizing soft tissue infection of his right forearm and previously undiagnosed diabetes mellitus. The infection progressively worsened to involve his right lateral chest wall despite multiple debridements and systemic antibiotics. His right arm was eventually disarticulated along with wide debridement of the surrounding tissue. Aggressive wound debridement, mechanical scrubbing, and irrigation were then initiated every 8 hours. A superoxidized solution was later introduced as a wound irrigant and dressing agent. The large defect was suitable for split-thickness skin grafting after 16 days of a strict wound management routine with the superoxidized solution.
  4. El-Faham A, Soliman SM, Osman SM, Ghabbour HA, Siddiqui MR, Fun HK, et al.
    PMID: 26845586 DOI: 10.1016/j.saa.2016.01.051
    Novel series of 2-(4,6-dimethoxy,1,3,5-triazin-2-yl) amino acid ester derivatives were synthesized using simple one pot method in methanol. The products were obtained in high yields and purities as observed from their spectral data, elemental analyses, GC-MS and X-ray crystallographic analysis. The B3LYP/6-311G(d,p) calculated molecular structures are well correlated with the geometrical parameters obtained from the X-ray analyses. The spectroscopic properties such as IR vibrational modes, NMR chemical shifts and UV-Vis electronic transitions were discussed both experimentally and theoretically. The IR vibrational frequencies showed good correlations with the experimental data (R(2)=0.9961-0.9995). The electronic spectra were assigned based on the TD-DFT results. Intense electronic transition band is calculated at 198.1nm (f=0.1389), 204.2nm (f=0.2053), 205.0 (f=0.1704) and 205.7 (0.2971) for compounds 6a-i, respectively. The molecular orbital energy levels contributed in the longest wavelength transition band were explained. For all compounds, the experimental wavelengths showed red shifts compared to the calculations due to the solvent effect. The NMR chemical shifts were calculated using GIAO method. The NBO analyses were performed to predict the stabilization energies due to the electron delocalization processes occur in the studied systems.
  5. Almomani E, Alabbadi I, Fasseeh A, Al-Qutob R, Al-Sharu E, Hayek N, et al.
    Value Health Reg Issues, 2021 Sep;25:126-134.
    PMID: 34015521 DOI: 10.1016/j.vhri.2021.01.003
    OBJECTIVES: Health technology assessment (HTA) can increase the appropriateness and transparency of pricing and reimbursement decisions. Jordan is still in the early phase of its HTA implementation, although the country has very limited public resources for the coverage of healthcare technologies. The study objective was to explore and validate priorities in the HTA road map for Jordan and propose to facilitate the preferred HTA status.

    METHODS: Health policy experts from the public and private sectors were asked to participate in a survey to explore the current and future status of HTA implementation in Jordan. Semistructured interviews with senior policy makers supported by literature review were conducted to validate survey results and make recommendations for specific actions.

    RESULTS: Survey and interview results indicated a need for increased HTA training, including both short courses and academic programs and gradually increasing public funding for technology assessment and appraisal. Multiple HTA bodies with central coordination can be the most feasible format of HTA institutionalization. The weight of cost-effectiveness criterion based on local data with published reports and explicit decision thresholds should be increased in policy decisions of pharmaceutical and nonpharmaceutical technologies.

    CONCLUSION: Currently, HTA has limited impact on health policy decisions in Jordan, and when it is used to support pharmaceutical reimbursement decisions, it is mainly based on results from other countries without considering transferability of international evidence. Policy makers should facilitate HTA institutionalization and use in policy decisions by increasing the weight of local evidence in HTA recommendations.

  6. Alani M, Altarturih H, Pars S, Al-Mhanawi B, Wolvetang EJ, Shaker MR
    Int J Stem Cells, 2024 Mar 27.
    PMID: 38531607 DOI: 10.15283/ijsc23170
    Stem cells and the cells they produce are unique because they vary from one cell to another. Traditional methods of studying cells often overlook these differences. However, the development of new technologies for studying individual cells has greatly changed biological research in recent years. Among these innovations, single-cell RNA sequencing (scRNA-seq) stands out. This technique allows scientists to examine the activity of genes in each cell, across thousands or even millions of cells. This makes it possible to understand the diversity of cells, identify new types of cells, and see how cells differ across different tissues, individuals, species, times, and conditions. This paper discusses the importance of scRNA-seq and the computational tools and software that are essential for analyzing the vast amounts of data generated by scRNA-seq studies. Our goal is to provide practical advice for bioinformaticians and biologists who are using scRNA-seq to study stem cells. We offer an overview of the scRNA-seq field, including the tools available, how they can be used, and how to present the results of these studies effectively. Our findings include a detailed overview and classification of tools used in scRNA-seq analysis, based on a review of 2,733 scientific publications. This review is complemented by information from the scRNA-tools database, which lists over 1,400 tools for analyzing scRNA-seq data. This database is an invaluable resource for researchers, offering a wide range of options for analyzing their scRNA-seq data.
  7. Braima KA, Sum JS, Ghazali AR, Muslimin M, Jeffery J, Lee WC, et al.
    PLoS One, 2013;8(10):e77924.
    PMID: 24194901 DOI: 10.1371/journal.pone.0077924
    BACKGROUND: The suburban transmission of malaria in Selangor, Malaysia's most developed and populous state still remains a concern for public health in this region. Despite much successful control efforts directed at its reduction, sporadic cases, mostly brought in by foreigners have continued to occur. In addition, cases of simian malaria caused by Plasmodium knowlesi, some with fatal outcome have caused grave concern to health workers. The aim of this study was to investigate the possibility of local malaria transmission in suburban regions of Selangor, which are adjacent to secondary rainforests.

    FINDINGS: A malaria survey spanning 7 years (2006 - 2012) was conducted in Selangor. A total of 1623 laboratory confirmed malaria cases were reported from Selangor's nine districts. While 72.6% of these cases (1178/1623) were attributed to imported malaria (cases originating from other countries), 25.5% (414/1623) were local cases and 1.9% (31/1623) were considered as relapse and unclassified cases combined. In this study, the most prevalent infection was P. vivax (1239 cases, prevalence 76.3%) followed by P. falciparum (211, 13.0%), P. knowlesi (75, 4.6%), P. malariae (71, 4.4%) and P. ovale (1, 0.06%). Mixed infections comprising of P. vivax and P. falciparum were confirmed (26, 1.6%). Entomological surveys targeting the residences of malaria patients' showed that the most commonly trapped Anopheles species was An. maculatus. No oocysts or sporozoites were found in the An. maculatus collected. Nevertheless, the possibility of An. maculatus being the malaria vector in the investigated locations was high due to its persistent occurrence in these areas.

    CONCLUSIONS: Malaria cases reported in this study were mostly imported cases. However the co-existence of local cases and potential Plasmodium spp. vectors should be cause for concern. The results of this survey reflect the need of maintaining closely monitored malaria control programs and continuous extensive malaria surveillance in Peninsula Malaysia.

  8. Pai YJ, Abdullah NL, Mohd-Zin SW, Mohammed RS, Rolo A, Greene ND, et al.
    PMID: 22945349 DOI: 10.1002/bdra.23072
    Adhesion and fusion of epithelial sheets marks the completion of many morphogenetic events during embryogenesis. Neural tube closure involves an epithelial fusion sequence in which the apposing neural folds adhere initially via cellular protrusions, proceed to a more stable union, and subsequently undergo remodeling of the epithelial structures to yield a separate neural tube roof plate and overlying nonneural ectoderm. Cellular protrusions comprise lamellipodia and filopodia, and studies in several different systems emphasize the critical role of RhoGTPases in their regulation. How epithelia establish initial adhesion is poorly understood but, in neurulation, may involve interactions between EphA receptors and their ephrinA ligands. Epithelial remodeling is spatially and temporally correlated with apoptosis in the dorsal neural tube midline, but experimental inhibition of this cell death does not prevent fusion and remodeling. A variety of molecular signaling systems have been implicated in the late events of morphogenesis, but genetic redundancy, for example among the integrins and laminins, makes identification of the critical players challenging. An improved understanding of epithelial fusion can provide insights into normal developmental processes and may also indicate the mode of origin of clinically important birth defects.
  9. Mohammed TJ, Albahri AS, Zaidan AA, Albahri OS, Al-Obaidi JR, Zaidan BB, et al.
    Appl Intell (Dordr), 2021;51(5):2956-2987.
    PMID: 34764579 DOI: 10.1007/s10489-020-02169-2
    As coronavirus disease 2019 (COVID-19) spreads across the world, the transfusion of efficient convalescent plasma (CP) to the most critical patients can be the primary approach to preventing the virus spread and treating the disease, and this strategy is considered as an intelligent computing concern. In providing an automated intelligent computing solution to select the appropriate CP for the most critical patients with COVID-19, two challenges aspects are bound to be faced: (1) distributed hospital management aspects (including scalability and management issues for prioritising COVID-19 patients and donors simultaneously), and (2) technical aspects (including the lack of COVID-19 dataset availability of patients and donors and an accurate matching process amongst them considering all blood types). Based on previous reports, no study has provided a solution for CP-transfusion-rescue intelligent framework during this pandemic that has addressed said challenges and issues. This study aimed to propose a novel CP-transfusion intelligent framework for rescuing COVID-19 patients across centralised/decentralised telemedicine hospitals based on the matching component process to provide an efficient CP from eligible donors to the most critical patients using multicriteria decision-making (MCDM) methods. A dataset, including COVID-19 patients/donors that have met the important criteria in the virology field, must be augmented to improve the developed framework. Four consecutive phases conclude the methodology. In the first phase, a new COVID-19 dataset is generated on the basis of medical-reference ranges by specialised experts in the virology field. The simulation data are classified into 80 patients and 80 donors on the basis of the five biomarker criteria with four blood types (i.e., A, B, AB, and O) and produced for COVID-19 case study. In the second phase, the identification scenario of patient/donor distributions across four centralised/decentralised telemedicine hospitals is identified 'as a proof of concept'. In the third phase, three stages are conducted to develop a CP-transfusion-rescue framework. In the first stage, two decision matrices are adopted and developed on the basis of the five 'serological/protein biomarker' criteria for the prioritisation of patient/donor lists. In the second stage, MCDM techniques are analysed to adopt individual and group decision making based on integrated AHP-TOPSIS as suitable methods. In the third stage, the intelligent matching components amongst patients/donors are developed on the basis of four distinct rules. In the final phase, the guideline of the objective validation steps is reported. The intelligent framework implies the benefits and strength weights of biomarker criteria to the priority configuration results and can obtain efficient CPs for the most critical patients. The execution of matching components possesses the scalability and balancing presentation within centralised/decentralised hospitals. The objective validation results indicate that the ranking is valid.
  10. Alsalem MA, Alamoodi AH, Albahri OS, Dawood KA, Mohammed RT, Alnoor A, et al.
    Artif Intell Rev, 2022 Jan 27.
    PMID: 35103030 DOI: 10.1007/s10462-021-10124-x
    The influence of the ongoing COVID-19 pandemic that is being felt in all spheres of our lives and has a remarkable effect on global health care delivery occurs amongst the ongoing global health crisis of patients and the required services. From the time of the first detection of infection amongst the public, researchers investigated various applications in the fight against the COVID-19 outbreak and outlined the crucial roles of different research areas in this unprecedented battle. In the context of existing studies in the literature surrounding COVID-19, related to medical treatment decisions, the dimensions of context addressed in previous multidisciplinary studies reveal the lack of appropriate decision mechanisms during the COVID-19 outbreak. Multiple criteria decision making (MCDM) has been applied widely in our daily lives in various ways with numerous successful stories to help analyse complex decisions and provide an accurate decision process. The rise of MCDM in combating COVID-19 from a theoretical perspective view needs further investigation to meet the important characteristic points that match integrating MCDM and COVID-19. To this end, a comprehensive review and an analysis of these multidisciplinary fields, carried out by different MCDM theories concerning COVID19 in complex case studies, are provided. Research directions on exploring the potentials of MCDM and enhancing its capabilities and power through two directions (i.e. development and evaluation) in COVID-19 are thoroughly discussed. In addition, Bibliometrics has been analysed, visualization and interpretation based on the evaluation and development category using R-tool involves; annual scientific production, country scientific production, Wordcloud, factor analysis in bibliographic, and country collaboration map. Furthermore, 8 characteristic points that go through the analysis based on new tables of information are highlighted and discussed to cover several important facts and percentages associated with standardising the evaluation criteria, MCDM theory in ranking alternatives and weighting criteria, operators used with the MCDM methods, normalisation types for the data used, MCDM theory contexts, selected experts ways, validation scheme for effective MCDM theory and the challenges of MCDM theory used in COVID-19 studies. Accordingly, a recommended MCDM theory solution is presented through three distinct phases as a future direction in COVID19 studies. Key phases of this methodology include the Fuzzy Delphi method for unifying criteria and establishing importance level, Fuzzy weighted Zero Inconsistency for weighting to mitigate the shortcomings of the previous weighting techniques and the MCDM approach by the name Fuzzy Decision by Opinion Score method for prioritising alternatives and providing a unique ranking solution. This study will provide MCDM researchers and the wider community an overview of the current status of MCDM evaluation and development methods and motivate researchers in harnessing MCDM potentials in tackling an accurate decision for different fields against COVID-19.
  11. Albahri AS, Albahri OS, Zaidan AA, Alnoor A, Alsattar HA, Mohammed R, et al.
    Comput Stand Interfaces, 2022 Mar;80:103572.
    PMID: 34456503 DOI: 10.1016/j.csi.2021.103572
    Owing to the limitations of Pythagorean fuzzy and intuitionistic fuzzy sets, scientists have developed a distinct and successive fuzzy set called the q-rung orthopair fuzzy set (q-ROFS), which eliminates restrictions encountered by decision-makers in multicriteria decision making (MCDM) methods and facilitates the representation of complex uncertain information in real-world circumstances. Given its advantages and flexibility, this study has extended two considerable MCDM methods the fuzzy-weighted zero-inconsistency (FWZIC) method and fuzzy decision by opinion score method (FDOSM) under the fuzzy environment of q-ROFS. The extensions were called q-rung orthopair fuzzy-weighted zero-inconsistency (q-ROFWZIC) method and q-rung orthopair fuzzy decision by opinion score method (q-ROFDOSM). The methodology formulated had two phases. The first phase 'development' presented the sequential steps of each method thoroughly.The q-ROFWZIC method was formulated and used in determining the weights of evaluation criteria and then integrated into the q-ROFDOSM for the prioritisation of alternatives on the basis of the weighted criteria. In the second phase, a case study regarding the MCDM problem of coronavirus disease 2019 (COVID-19) vaccine distribution was performed. The purpose was to provide fair allocation of COVID-19 vaccine doses. A decision matrix based on an intersection of 'recipients list' and 'COVID-19 distribution criteria' was adopted. The proposed methods were evaluated according to systematic ranking assessment and sensitivity analysis, which revealed that the ranking was subject to a systematic ranking that is supported by high correlation results over different scenarios with variations in the weights of criteria.
  12. Alsalem MA, Alsattar HA, Albahri AS, Mohammed RT, Albahri OS, Zaidan AA, et al.
    J Infect Public Health, 2021 Oct;14(10):1513-1559.
    PMID: 34538731 DOI: 10.1016/j.jiph.2021.08.026
    The problem complexity of multi-criteria decision-making (MCDM) has been raised in the distribution of coronavirus disease 2019 (COVID-19) vaccines, which required solid and robust MCDM methods. Compared with other MCDM methods, the fuzzy-weighted zero-inconsistency (FWZIC) method and fuzzy decision by opinion score method (FDOSM) have demonstrated their solidity in solving different MCDM challenges. However, the fuzzy sets used in these methods have neglected the refusal concept and limited the restrictions on their constants. To end this, considering the advantage of the T-spherical fuzzy sets (T-SFSs) in handling the uncertainty in the data and obtaining information with more degree of freedom, this study has extended FWZIC and FDOSM methods into the T-SFSs environment (called T-SFWZIC and T-SFDOSM) to be used in the distribution of COVID-19 vaccines. The methodology was formulated on the basis of decision matrix adoption and development phases. The first phase described the adopted decision matrix used in the COVID-19 vaccine distribution. The second phase presented the sequential formulation steps of T-SFWZIC used for weighting the distribution criteria followed by T-SFDOSM utilised for prioritising the vaccine recipients. Results revealed the following: (1) T-SFWZIC effectively weighted the vaccine distribution criteria based on several parameters including T = 2, T = 4, T = 6, T = 8, and T = 10. Amongst all parameters, the age criterion received the highest weight, whereas the geographic locations severity criterion has the lowest weight. (2) According to the T parameters, a considerable variance has occurred on the vaccine recipient orders, indicating that the existence of T values affected the vaccine distribution. (3) In the individual context of T-SFDOSM, no unique prioritisation was observed based on the obtained opinions of each expert. (4) The group context of T-SFDOSM used in the prioritisation of vaccine recipients was considered the final distribution result as it unified the differences found in an individual context. The evaluation was performed based on systematic ranking assessment and sensitivity analysis. This evaluation showed that the prioritisation results based on each T parameter were subject to a systematic ranking that is supported by high correlation results over all discussed scenarios of changing criteria weights values.
  13. Alamoodi AH, Zaidan BB, Albahri OS, Garfan S, Ahmaro IYY, Mohammed RT, et al.
    PMID: 36777815 DOI: 10.1007/s40747-023-00972-1
    When COVID-19 spread in China in December 2019, thousands of studies have focused on this pandemic. Each presents a unique perspective that reflects the pandemic's main scientific disciplines. For example, social scientists are concerned with reducing the psychological impact on the human mental state especially during lockdown periods. Computer scientists focus on establishing fast and accurate computerized tools to assist in diagnosing, preventing, and recovering from the disease. Medical scientists and doctors, or the frontliners, are the main heroes who received, treated, and worked with the millions of cases at the expense of their own health. Some of them have continued to work even at the expense of their lives. All these studies enforce the multidisciplinary work where scientists from different academic disciplines (social, environmental, technological, etc.) join forces to produce research for beneficial outcomes during the crisis. One of the many branches is computer science along with its various technologies, including artificial intelligence, Internet of Things, big data, decision support systems (DSS), and many more. Among the most notable DSS utilization is those related to multicriterion decision making (MCDM), which is applied in various applications and across many contexts, including business, social, technological and medical. Owing to its importance in developing proper decision regimens and prevention strategies with precise judgment, it is deemed a noteworthy topic of extensive exploration, especially in the context of COVID-19-related medical applications. The present study is a comprehensive review of COVID-19-related medical case studies with MCDM using a systematic review protocol. PRISMA methodology is utilized to obtain a final set of (n = 35) articles from four major scientific databases (ScienceDirect, IEEE Xplore, Scopus, and Web of Science). The final set of articles is categorized into taxonomy comprising five groups: (1) diagnosis (n = 6), (2) safety (n = 11), (3) hospital (n = 8), (4) treatment (n = 4), and (5) review (n = 3). A bibliographic analysis is also presented on the basis of annual scientific production, country scientific production, co-occurrence, and co-authorship. A comprehensive discussion is also presented to discuss the main challenges, motivations, and recommendations in using MCDM research in COVID-19-related medial case studies. Lastly, we identify critical research gaps with their corresponding solutions and detailed methodologies to serve as a guide for future directions. In conclusion, MCDM can be utilized in the medical field effectively to optimize the resources and make the best choices particularly during pandemics and natural disasters.
  14. Alsalem MA, Mohammed R, Albahri OS, Zaidan AA, Alamoodi AH, Dawood K, et al.
    Int J Intell Syst, 2022 Jun;37(6):3514-3624.
    PMID: 38607836 DOI: 10.1002/int.22699
    Considering the coronavirus disease 2019 (COVID-19) pandemic, the government and health sectors are incapable of making fast and reliable decisions, particularly given the various effects of decisions on different contexts or countries across multiple sectors. Therefore, leaders often seek decision support approaches to assist them in such scenarios. The most common decision support approach used in this regard is multiattribute decision-making (MADM). MADM can assist in enforcing the most ideal decision in the best way possible when fed with the appropriate evaluation criteria and aspects. MADM also has been of great aid to practitioners during the COVID-19 pandemic. Moreover, MADM shows resilience in mitigating consequences in health sectors and other fields. Therefore, this study aims to analyse the rise of MADM techniques in combating COVID-19 by presenting a systematic literature review of the state-of-the-art COVID-19 applications. Articles on related topics were searched in four major databases, namely, Web of Science, IEEE Xplore, ScienceDirect, and Scopus, from the beginning of the pandemic in 2019 to April 2021. Articles were selected on the basis of the inclusion and exclusion criteria for the identified systematic review protocol, and a total of 51 articles were obtained after screening and filtering. All these articles were formed into a coherent taxonomy to describe the corresponding current standpoints in the literature. This taxonomy was drawn on the basis of four major categories, namely, medical (n = 30), social (n = 4), economic (n = 13) and technological (n = 4). Deep analysis for each category was performed in terms of several aspects, including issues and challenges encountered, contributions, data set, evaluation criteria, MADM techniques, evaluation and validation and bibliography analysis. This study emphasised the current standpoint and opportunities for MADM in the midst of the COVID-19 pandemic and promoted additional efforts towards understanding and providing new potential future directions to fulfil the needs of this study field.
  15. Albahri OS, Al-Obaidi JR, Zaidan AA, Albahri AS, Zaidan BB, Salih MM, et al.
    Comput Methods Programs Biomed, 2020 Nov;196:105617.
    PMID: 32593060 DOI: 10.1016/j.cmpb.2020.105617
    CONTEXT: People who have recently recovered from the threat of deteriorating coronavirus disease-2019 (COVID-19) have antibodies to the coronavirus circulating in their blood. Thus, the transfusion of these antibodies to deteriorating patients could theoretically help boost their immune system. Biologically, two challenges need to be surmounted to allow convalescent plasma (CP) transfusion to rescue the most severe COVID-19 patients. First, convalescent subjects must meet donor selection plasma criteria and comply with national health requirements and known standard routine procedures. Second, multi-criteria decision-making (MCDM) problems should be considered in the selection of the most suitable CP and the prioritisation of patients with COVID-19.

    OBJECTIVE: This paper presents a rescue framework for the transfusion of the best CP to the most critical patients with COVID-19 on the basis of biological requirements by using machine learning and novel MCDM methods.

    METHOD: The proposed framework is illustrated on the basis of two distinct and consecutive phases (i.e. testing and development). In testing, ABO compatibility is assessed after classifying donors into the four blood types, namely, A, B, AB and O, to indicate the suitability and safety of plasma for administration in order to refine the CP tested list repository. The development phase includes patient and donor sides. In the patient side, prioritisation is performed using a contracted patient decision matrix constructed between 'serological/protein biomarkers and the ratio of the partial pressure of oxygen in arterial blood to fractional inspired oxygen criteria' and 'patient list based on novel MCDM method known as subjective and objective decision by opinion score method'. Then, the patients with the most urgent need are classified into the four blood types and matched with a tested CP list from the test phase in the donor side. Thereafter, the prioritisation of CP tested list is performed using the contracted CP decision matrix.

    RESULT: An intelligence-integrated concept is proposed to identify the most appropriate CP for corresponding prioritised patients with COVID-19 to help doctors hasten treatments.

    DISCUSSION: The proposed framework implies the benefits of providing effective care and prevention of the extremely rapidly spreading COVID-19 from affecting patients and the medical sector.

  16. Albahri OS, Zaidan AA, Albahri AS, Alsattar HA, Mohammed R, Aickelin U, et al.
    J Adv Res, 2022 Mar;37:147-168.
    PMID: 35475277 DOI: 10.1016/j.jare.2021.08.009
    INTRODUCTION: The vaccine distribution for the COVID-19 is a multicriteria decision-making (MCDM) problem based on three issues, namely, identification of different distribution criteria, importance criteria and data variation. Thus, the Pythagorean fuzzy decision by opinion score method (PFDOSM) for prioritising vaccine recipients is the correct approach because it utilises the most powerful MCDM ranking method. However, PFDOSM weighs the criteria values of each alternative implicitly, which is limited to explicitly weighting each criterion. In view of solving this theoretical issue, the fuzzy-weighted zero-inconsistency (FWZIC) can be used as a powerful weighting MCDM method to provide explicit weights for a criteria set with zero inconstancy. However, FWZIC is based on the triangular fuzzy number that is limited in solving the vagueness related to the aforementioned theoretical issues.

    OBJECTIVES: This research presents a novel homogeneous Pythagorean fuzzy framework for distributing the COVID-19 vaccine dose by integrating a new formulation of the PFWZIC and PFDOSM methods.

    METHODS: The methodology is divided into two phases. Firstly, an augmented dataset was generated that included 300 recipients based on five COVID-19 vaccine distribution criteria (i.e., vaccine recipient memberships, chronic disease conditions, age, geographic location severity and disabilities). Then, a decision matrix was constructed on the basis of an intersection of the 'recipients list' and 'COVID-19 distribution criteria'. Then, the MCDM methods were integrated. An extended PFWZIC was developed, followed by the development of PFDOSM.

    RESULTS: (1) PFWZIC effectively weighted the vaccine distribution criteria. (2) The PFDOSM-based group prioritisation was considered in the final distribution result. (3) The prioritisation ranks of the vaccine recipients were subject to a systematic ranking that is supported by high correlation results over nine scenarios of the changing criteria weights values.

    CONCLUSION: The findings of this study are expected to ensuring equitable protection against COVID-19 and thus help accelerate vaccine progress worldwide.

  17. MalariaGEN, Adam I, Alam MS, Alemu S, Amaratunga C, Amato R, et al.
    Wellcome Open Res, 2022;7:136.
    PMID: 35651694 DOI: 10.12688/wellcomeopenres.17795.1
    This report describes the MalariaGEN Pv4 dataset, a new release of curated genome variation data on 1,895 samples of Plasmodium vivax collected at 88 worldwide locations between 2001 and 2017. It includes 1,370 new samples contributed by MalariaGEN and VivaxGEN partner studies in addition to previously published samples from these and other sources. We provide genotype calls at over 4.5 million variable positions including over 3 million single nucleotide polymorphisms (SNPs), as well as short indels and tandem duplications. This enlarged dataset highlights major compartments of parasite population structure, with clear differentiation between Africa, Latin America, Oceania, Western Asia and different parts of Southeast Asia. Each sample has been classified for drug resistance to sulfadoxine, pyrimethamine and mefloquine based on known markers at the dhfr, dhps and mdr1 loci. The prevalence of all of these resistance markers was much higher in Southeast Asia and Oceania than elsewhere. This open resource of analysis-ready genome variation data from the MalariaGEN and VivaxGEN networks is driven by our collective goal to advance research into the complex biology of P. vivax and to accelerate genomic surveillance for malaria control and elimination.
  18. Trimarsanto H, Amato R, Pearson RD, Sutanto E, Noviyanti R, Trianty L, et al.
    Commun Biol, 2022 Dec 23;5(1):1411.
    PMID: 36564617 DOI: 10.1038/s42003-022-04352-2
    Traditionally, patient travel history has been used to distinguish imported from autochthonous malaria cases, but the dormant liver stages of Plasmodium vivax confound this approach. Molecular tools offer an alternative method to identify, and map imported cases. Using machine learning approaches incorporating hierarchical fixation index and decision tree analyses applied to 799 P. vivax genomes from 21 countries, we identified 33-SNP, 50-SNP and 55-SNP barcodes (GEO33, GEO50 and GEO55), with high capacity to predict the infection's country of origin. The Matthews correlation coefficient (MCC) for an existing, commonly applied 38-SNP barcode (BR38) exceeded 0.80 in 62% countries. The GEO panels outperformed BR38, with median MCCs > 0.80 in 90% countries at GEO33, and 95% at GEO50 and GEO55. An online, open-access, likelihood-based classifier framework was established to support data analysis (vivaxGEN-geo). The SNP selection and classifier methods can be readily amended for other use cases to support malaria control programs.
Related Terms
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links