Displaying publications 1 - 20 of 312 in total

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  1. Ab Ghani NS, Emrizal R, Makmur H, Firdaus-Raih M
    Comput Struct Biotechnol J, 2020;18:2931-2944.
    PMID: 33101604 DOI: 10.1016/j.csbj.2020.10.013
    Structures of protein-drug-complexes provide an atomic level profile of drug-target interactions. In this work, the three-dimensional arrangements of amino acid side chains in known drug binding sites (substructures) were used to search for similarly arranged sites in SARS-CoV-2 protein structures in the Protein Data Bank for the potential repositioning of approved compounds. We were able to identify 22 target sites for the repositioning of 16 approved drug compounds as potential therapeutics for COVID-19. Using the same approach, we were also able to investigate the potentially promiscuous binding of the 16 compounds to off-target sites that could be implicated in toxicity and side effects that had not been provided by any previous studies. The investigations of binding properties in disease-related proteins derived from the comparison of amino acid substructure arrangements allows for effective mechanism driven decision making to rank and select only the compounds with the highest potential for success and safety to be prioritized for clinical trials or treatments. The intention of this work is not to explicitly identify candidate compounds but to present how an integrated drug repositioning and potential toxicity pipeline using side chain similarity searching algorithms are of great utility in epidemic scenarios involving novel pathogens. In the case of the COVID-19 pandemic caused by the SARS-CoV-2 virus, we demonstrate that the pipeline can identify candidate compounds quickly and sustainably in combination with associated risk factors derived from the analysis of potential off-target site binding by the compounds to be repurposed.
    Matched MeSH terms: Decision Making
  2. Abdul Rauf Abdul Rasam, Noresah Mohd Shariff, Dony, Jiloris F., Saiful Aman Sulaiman
    Jurnal Inovasi Malaysia, 2018;2(1):75-88.
    MyJurnal
    An innovative health information system can be used to support the control of tuberculosis (TB) in Malaysia. The existing system of MyTB has helped in the national TB information management and decision-making process. However, the system can be further enhanced by producing a prototype of Geospatial Tuberculosis Information System (GeoTBiS). It is a geospatial decision support system that was initially proposed in Shah Alam, Selangor. Geospatial data has spatio-temporal characteristics that can be used to understand the basic elements of TB aetiology, while geospatial operations are employed to collect, manage and disseminate the data in a geographical information system (GIS) environment. The disease map and epidemiological risk analysis are produced using a global positioning system (GPS), satellite imagery, geostatistical analysis and web mapping services. This GeoTBiS has demonstrated the geospatial capabilities in enhancing the current system functions, and several recommendations towards a practicable application.
    Matched MeSH terms: Decision Making
  3. Abdullah A, Abdullah KL, Yip CH, Teo SH, Taib NA, Ng CJ
    Asian Pac J Cancer Prev, 2013;14(12):7143-7.
    PMID: 24460266
    BACKGROUND: The survival outcomes for women presenting with early breast cancer are influenced by treatment decisions. In Malaysia, survival outcome is generally poor due to late presentation. Of those who present early, many refuse treatment for complementary therapy.
    OBJECTIVE: This study aimed to explore the decision making experiences of women with early breast cancer.
    MATERIALS AND METHODS: A qualitative study using individual in-depth interviews was conducted to capture the decision making process of women with early breast cancer in Malaysia. We used purposive sampling to recruit women yet to undergo surgical treatment. A total of eight participants consented and were interviewed using a semi-structured interview guide. These women were recruited from a period of one week after they were informed of their diagnoses. A topic guide, based on the Ottawa decision support framework (ODSF), was used to facilitate the interviews, which were audio recorded, transcribed and analysed using a thematic approach.
    RESULTS: We identified four phases in the decision-making process of women with early breast cancer: discovery (pre-diagnosis); confirmatory ('receiving bad news'); deliberation; and decision (making a decision). These phases ranged from when women first discovered abnormalities in their breasts to them making final surgical treatment decisions. Information was vital in guiding these women. Support from family members, friends, healthcare professionals as well as survivors also has an influencing role. However, the final say on treatment decision was from themselves.
    CONCLUSIONS: The treatment decision for women with early breast cancer in Malaysia is a result of information they gather on their decision making journey. This journey starts with diagnosis. The women's spouses, friends, family members and healthcare professionals play different roles as information providers and supporters at different stages of treatment decisions. However, the final treatment decision is influenced mainly by women's own experiences, knowledge and understanding.
    Study site: Breast surgical units, Klang Valley, Malaysia
    Matched MeSH terms: Decision Making*
  4. Aborigo RA, Reidpath DD, Oduro AR, Allotey P
    BMC Pregnancy Childbirth, 2018 01 02;18(1):3.
    PMID: 29291711 DOI: 10.1186/s12884-017-1641-9
    BACKGROUND: Twenty years after acknowledging the importance of joint responsibilities and male participation in maternal health programs, most health care systems in low income countries continue to face challenges in involving men. We explored the reasons for men's resistance to the adoption of a more proactive role in pregnancy care and their enduring influence in the decision making process during emergencies.

    METHODS: Ten focus group discussions were held with opinion leaders (chiefs, elders, assemblymen, leaders of women groups) and 16 in-depth interviews were conducted with healthcare workers (District Directors of Health, Medical Assistants in-charge of health centres, and district Public Health Nurses and Midwives). The interviews and discussions were audio recorded, transcribed into English and imported into NVivo 10 for content analysis.

    RESULTS: As heads of the family, men control resources, consult soothsayers to determine the health seeking or treatment for pregnant women, and serve as the final authority on where and when pregnant women should seek medical care. Beyond that, they have no expectation of any further role during antenatal care and therefore find it unnecessary to attend clinics with their partners. There were conflicting views about whether men needed to provide any extra support to their pregnant partners within the home. Health workers generally agreed that men provided little or no support to their partners. Although health workers had facilitated the formation of father support groups, there was little evidence of any impact on antenatal support.

    CONCLUSIONS: In patriarchal settings, the role of men can be complex and social and cultural traditions may conflict with public health recommendations. Initiatives to promote male involvement should focus on young men and use chiefs and opinion leaders as advocates to re-orient men towards more proactive involvement in ensuring the health of their partners.

    Matched MeSH terms: Decision Making
  5. Abousheishaa AA, Lazim NHM, Tang SL, Sulaiman AH, Huri HZ, Guan NC
    Patient Educ Couns, 2022 Jul;105(7):2466-2474.
    PMID: 34844812 DOI: 10.1016/j.pec.2021.11.007
    OBJECTIVES: This study aimed to develop and assess the effectiveness of an encounter decision aid for Malaysian patients with MDD to support treatment decision-making during the consultation.

    METHODS: The decision aid prototype was developed following a literature review and six focus groups. Alpha testing assessed its comprehensibility, acceptability, usability and desirability through user-centered cognitive interviews. Beta-testing evaluated preliminary evidence on its efficacy using the SDM Scale and PDMS. Feasibility was assessed by timing the consultation.

    RESULTS: The alpha testing demonstrated that the decision aid was patient-oriented, comprehensible, comprehensive, concise and objective with an appealing design. Beta-testing indicated that PtDA significantly increased patients satisfaction with SDM from patients' [83.32 (13.92) vs 85.76 (13.80); p 

    Matched MeSH terms: Decision Making
  6. Abu Kasim NH, Abu Kassim NL, Razak AA, Abdullah H, Bindal P, Che' Abdul Aziz ZA, et al.
    Eur J Dent Educ, 2014 Feb;18(1):51-7.
    PMID: 24423176 DOI: 10.1111/eje.12058
    Training dentists today is challenging as they are expected to provide a wide range of dental care. In the provision of good dental care, soft skills are equally important as clinical skills. Therefore in dental education the development of soft skills are of prime concern. This study sought to identify the development of soft skills when dental students are paired in their clinical training. In this perception study, four open-ended items were used to elicit students' feedback on the appropriateness of using clinical pairing as an instructional strategy to promote soft skills. The most frequently cited soft skills were teamwork (70%) and communication (25%) skills. However, both negative and positive behaviours were reported. As for critical thinking and problem solving skills, more positive behaviours were reported for abilities such as to explain, analyze, find ideas and alternative solutions, and make decisions. Leadership among peers was not evident as leading without legitimate authority could be a hindrance to its development. If clinical pairing is to be used as an effective instructional strategy to promote soft skills amongst students, clear guidelines need to be developed to prepare students to work in a dental team and the use of appropriate assessment tools can facilitate the development of these soft skills.
    Matched MeSH terms: Decision Making
  7. Adams-Guppy J, Guppy A
    Ergonomics, 2003 Jun 20;46(8):763-79.
    PMID: 12745978 DOI: 10.1080/0014013021000056980
    As part of an organizational review of safety, interviews and questionnaire surveys were performed on over 700 commercial goods drivers and their managers within a series of related companies operating across 17 countries. The results examine the reported incidence of fatigue-related problems in drivers and their associations with near miss and accident experience as well as work and organizational factors. Experience of fatigue problems while driving was linked to time of day and rotation of shifts, though most associations were small. There were significant associations found between fatigue experiences and driver and management systems of break taking and route scheduling. The quantitative combined with qualitative information suggested that, where feasible, more flexible approaches to managing the scheduling and sequencing of deliveries assisted drivers in managing their own fatigue problems through appropriate break-taking. The results are interpreted within the overarching principles of risk assessment and risk control.
    Matched MeSH terms: Decision Making
  8. Adeshina AM, Hashim R, Khalid NE
    Interdiscip Sci, 2014 Sep;6(3):222-34.
    PMID: 25205500 DOI: 10.1007/s12539-013-0204-7
    Hepatocellular Carcinoma is the most common type of liver cancer having a strong relation with cirrhosis. Undoubtedly, cirrhosis may be caused by the virus infection of hepatitis B (HBV) and hepatitis C (HBC) or through alchoholism. However, even when cirrhosis has not been developed, patients with hepatitis viral infections are still at the risk of liver cancer. Apparently, among the numerous medical imaging techniques, Computed Tomography (CT) is the best in defining liver tumor borders. Unfortunately, these imaging techniques, including the CT procedures, usually rely on an appended application to reconstruct the generated 2-D slices to 3-D model. This may involve high performance computation, may be time-consuming or costly. Moreover, even with the outstanding performances of CT in defining the liver tumor boundaries, contrast between tumor tissues and the surrounding liver parenchyma is too low in CT slices. With such a close proxity in the tumor and the surrounding liver tissues, accurate characterization of liver tumor is a challenge. Previously, algorithms were developed to reveal abnormalities in brain's MRI datasets and CT abdominal pelvic, however, introducing a framework that could accurately characterize liver tumor and its surrounding tissues in CT datasets would go a long way in contributing to medical diagnosis and therapy planning of Hepatocellular Carcinoma. This paper proposes an Hepatocellular Carcinoma framework by extending the functionalities of SurLens Visualization System with an automatic liver tumor localization technique using Compute Unified Device Architecture (CUDA). The study was evaluated with liver CT datasets from the Imaging Science and Information Systems (ISIS) Center, the Georgetown University Medical Center. Significantly, visualization of liver CT datasets and the localization of the entangled tumor was achieved without prior datasets segmentation. Interestingly, the framework achieved remarkably good processing speed at a reasonably cheaper cost with an immediate reconstruction of the datasets and mapping of the tumor tissues within the surrounding liver parenchyma.
    Matched MeSH terms: Decision Making, Computer-Assisted*
  9. Adlina, S., Narimah, A.H.H., Hakimi, Z.A., N Adilah, H., N Syuhada, Y.
    MyJurnal
    Employee satnfaction surveys can provide the information needed to improved levek of productivity, job and loyalty. Management can identify the factors of job issues and provide solutions to improve the working environment. A cross sectional descriptive study on employee satisfaction among a health care district office’s staff was conducted in Perak in March - April 2006. A total of 19 staff were randomly picked and interviewed in the data collection process. Almost all understand the objectives of the administration unit (94%) and were satisfied with the management leadership’s style (78%- l 00%) . Majority agreed that their relationship with immediate superior and within the group was harmonious and professional (89%) and they preferred an open problem solving method in handling conflict (72 %). The most common type of incentive rewarded by the administration to express gratitude to their staff was certificate (56%); bonus and medal (33%); and informal gesture (28%). Majority (83%) were also satisfied by the method used to disseminate the information in their units. Majority agreed that the working environment in the administration unit were conducive (72%), their ideas were equally considered during decision making sessions (89%) and training opportunities were similarly given to them by the management (72%). This study revealed that employee satisfaction was determined by several factors such as management leadership's style, opportunity to contribute skills and idea; reward and incentive; and conducive king environment.
    Matched MeSH terms: Decision Making
  10. Aghajani Mir M, Taherei Ghazvinei P, Sulaiman NM, Basri NE, Saheri S, Mahmood NZ, et al.
    J Environ Manage, 2016 Jan 15;166:109-15.
    PMID: 26496840 DOI: 10.1016/j.jenvman.2015.09.028
    Selecting a suitable Multi Criteria Decision Making (MCDM) method is a crucial stage to establish a Solid Waste Management (SWM) system. Main objective of the current study is to demonstrate and evaluate a proposed method using Multiple Criteria Decision Making methods (MCDM). An improved version of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) applied to obtain the best municipal solid waste management method by comparing and ranking the scenarios. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Besides, Viekriterijumsko Kompromisno Rangiranje (VIKOR) compromise solution method applied for sensitivity analyses. The proposed method can assist urban decision makers in prioritizing and selecting an optimized Municipal Solid Waste (MSW) treatment system. Besides, a logical and systematic scientific method was proposed to guide an appropriate decision-making. A modified TOPSIS methodology as a superior to existing methods for first time was applied for MSW problems. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Next, 11 scenarios of MSW treatment methods are defined and compared environmentally and economically based on the waste management conditions. Results show that integrating a sanitary landfill (18.1%), RDF (3.1%), composting (2%), anaerobic digestion (40.4%), and recycling (36.4%) was an optimized model of integrated waste management. An applied decision-making structure provides the opportunity for optimum decision-making. Therefore, the mix of recycling and anaerobic digestion and a sanitary landfill with Electricity Production (EP) are the preferred options for MSW management.
    Matched MeSH terms: Decision Making
  11. Ahmad, K.I., Shamsul, A.S., Ismail, M.S.
    MyJurnal
    Acute appendicitis is one of the most common differential diagnoses for acute abdominal pain made by emergency doctors. Suspected cases require surgical referral for observation or definitive intervention to prevent complications. A high index of suspicion and good clinical skills with the aid of scoring systems allows early decision making, which includes optimal pain control. The objective of this study was to identify the pain score and is relationship to the cut-off points of the Alvarado scoring system so that justifies early surgical referral or discharge for suspected acute appendicitis from the Emergency Department of Universiti Kebangsaan Malaysia Medical Centre (UKMMC). This was a cross sectional study of acute abdominal pain from June 2007 to September 2008. All patients who fulfilled the criteria and consented to the study were assessed for Alvarado score, verbal numerical pain score (VNRS) and their subsequent management. Patients with an Alvarado score of ≥7 were likely to have acute appendicitis (80.1% sensitivity and 52.63% specificity) and those with the score of ≤3 were unlikely to have acute appendicitis. The median pain score was 7.00 (IQR: 5.00-8.50) but 72.5% did not receive any analgesia. There was no direct relationship between the pain score with Alvarado score. Oligoanalgesia in patients with acute appendicitis still exist in Emergency Department of UKMMC.
    Matched MeSH terms: Decision Making
  12. Ahmadi H, Nilashi M, Ibrahim O
    Int J Med Inform, 2015 Mar;84(3):166-88.
    PMID: 25612792 DOI: 10.1016/j.ijmedinf.2014.12.004
    This study mainly integrates the mature Technology-Organization-Environment (TOE) framework and recently developed Human-Organization-Technology (HOT) fit model to identify factors that affect the hospital decision in adopting Hospital Information System (HIS).
    Matched MeSH terms: Decision Making, Organizational*
  13. Al-Areefi MA, Hassali MA, Mohamed Ibrahim MI
    Res Social Adm Pharm, 2013 Nov-Dec;9(6):981-8.
    PMID: 23218551 DOI: 10.1016/j.sapharm.2012.10.006
    Prescribing decisions are a complex phenomenon and influenced by many pharmacological and non-pharmacological factors. Little is known about the actual prescribing behaviors of physicians or the factors behind their prescribing decisions.
    Matched MeSH terms: Decision Making
  14. Al-Rawi HA, Yau KL, Mohamad H, Ramli N, Hashim W
    ScientificWorldJournal, 2014;2014:960584.
    PMID: 25140350 DOI: 10.1155/2014/960584
    Cognitive radio (CR) enables unlicensed users (or secondary users, SUs) to sense for and exploit underutilized licensed spectrum owned by the licensed users (or primary users, PUs). Reinforcement learning (RL) is an artificial intelligence approach that enables a node to observe, learn, and make appropriate decisions on action selection in order to maximize network performance. Routing enables a source node to search for a least-cost route to its destination node. While there have been increasing efforts to enhance the traditional RL approach for routing in wireless networks, this research area remains largely unexplored in the domain of routing in CR networks. This paper applies RL in routing and investigates the effects of various features of RL (i.e., reward function, exploitation, and exploration, as well as learning rate) through simulation. New approaches and recommendations are proposed to enhance the features in order to improve the network performance brought about by RL to routing. Simulation results show that the RL parameters of the reward function, exploitation, and exploration, as well as learning rate, must be well regulated, and the new approaches proposed in this paper improves SUs' network performance without significantly jeopardizing PUs' network performance, specifically SUs' interference to PUs.
    Matched MeSH terms: Decision Making, Computer-Assisted
  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.

    Matched MeSH terms: Decision Making
  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.

    Matched MeSH terms: Decision Making
  17. Alden DL, Friend J, Lee PY, Lee YK, Trevena L, Ng CJ, et al.
    Med Decis Making, 2018 01;38(1):14-25.
    PMID: 28691551 DOI: 10.1177/0272989X17715628
    BACKGROUND: Research suggests that desired family involvement (FI) in medical decision making may depend on cultural values. Unfortunately, the field lacks cross-cultural studies that test this assumption. As a result, providers may be guided by incomplete information or cultural biases rather than patient preferences.

    METHODS: Researchers developed 6 culturally relevant disease scenarios varying from low to high medical seriousness. Quota samples of approximately 290 middle-aged urban residents in Australia, China, Malaysia, India, South Korea, Thailand, and the USA completed an online survey that examined desired levels of FI and identified individual difference predictors in each country. All reliability coefficients were acceptable. Regression models met standard assumptions.

    RESULTS: The strongest finding across all 7 countries was that those who desired higher self-involvement (SI) in medical decision making also wanted lower FI. On the other hand, respondents who valued relational-interdependence tended to want their families involved - a key finding in 5 of 7 countries. In addition, in 4 of 7 countries, respondents who valued social hierarchy desired higher FI. Other antecedents were less consistent.

    CONCLUSION: These results suggest that it is important for health providers to avoid East-West cultural stereotypes. There are meaningful numbers of patients in all 7 countries who want to be individually involved and those individuals tend to prefer lower FI. On the other hand, more interdependent patients are likely to want families involved in many of the countries studied. Thus, individual differences within culture appear to be important in predicting whether a patient desires FI. For this reason, avoiding culture-based assumptions about desired FI during medical decision making is central to providing more effective patient centered care.

    Matched MeSH terms: Decision Making*
  18. Aljunid SM, Srithamrongsawat S, Chen W, Bae SJ, Pwu RF, Ikeda S, et al.
    Value Health, 2012 2 1;15(1 Suppl):S132-8.
    PMID: 22265060 DOI: 10.1016/j.jval.2011.11.004
    This article sought to describe the health-care data situation in six selected economies in the Asia-Pacific region. Authors from Thailand, China mainland, South Korea, Taiwan, Japan, and Malaysia present their analyses in three parts. The first part of the article describes the data-collection process and the sources of data. The second part of the article presents issues around policies of data sharing with the stakeholders. The third and final part of the article focuses on the extent of health-care data use for policy reform in these different economies. Even though these economies differ in their economic structure and population size, they share some similarities on issues related to health-care data. There are two main institutions that collect and manage the health-care data in these economies. In Thailand, China mainland, Taiwan, and Malaysia, the Ministry of Health is responsible through its various agencies for collecting and managing the health-care data. On the other hand, health insurance is the main institution that collects and stores health-care data in South Korea and Japan. In all economies, sharing of and access to data is an issue. The reasons for limited access to some data are privacy protection, fragmented health-care system, poor quality of routinely collected data, unclear policies and procedures to access the data, and control on the freedom on publication. The primary objective of collecting health-care data in these economies is to aid the policymakers and researchers in policy decision making as well as create an awareness on health-care issues for the general public. The usage of data in monitoring the performance of the heath system is still in the process of development. In conclusion, for the region under discussion, health-care data collection is under the responsibility of the Ministry of Health and health insurance agencies. Data are collected from health-care providers mainly from the public sector. Routinely collected data are supplemented by national surveys. Accessibility to the data is a major issue in most of the economies under discussion. Accurate health-care data are required mainly to support policy making and evidence-based decisions.
    Matched MeSH terms: Decision Making
  19. Allawi MF, Aidan IA, El-Shafie A
    Environ Sci Pollut Res Int, 2021 Feb;28(7):8281-8295.
    PMID: 33052565 DOI: 10.1007/s11356-020-11062-x
    The accuracy level for reservoir evaporation prediction is an important issue for decision making in the water resources field. The traditional methods for evaporation prediction could encounter numerous obstacles owing to the effect of several parameters on the shape of the evaporation pattern. The current research presented modern model called the Coactive Neuro-Fuzzy Inference System (CANFIS). Modification for such model has been achieved for enhancing the evaporation prediction accuracy. Genetic algorithm was utilized to select the effective input combination. The efficiency of the proposed model has been compared with popular artificial intelligence models according to several statistical indicators. Two different case studies Aswan High Dam (AHD) and Timah Tasoh Dam (TTD) have been considered to explore the performance of the proposed models. It is concluded that the modified GA-CANFIS model is better than GA-ANFIS, GA-SVR, and GA-RBFNN for evaporation prediction for both case studies. GA-CANFIS attained minimum RMSE (15.22 mm month-1 for AHD, 8.78 mm month-1 for TTD), minimum MAE (12.48 mm month-1 for AHD, 5.11 mm month-1 for TTD), and maximum determination coefficient (0.98 for AHD, 0.95 for TTD).
    Matched MeSH terms: Decision Making
  20. Almahdi EM, Zaidan AA, Zaidan BB, Alsalem MA, Albahri OS, Albahri AS
    J Med Syst, 2019 Jun 06;43(7):219.
    PMID: 31172296 DOI: 10.1007/s10916-019-1339-9
    This study presents a prioritisation framework for mobile patient monitoring systems (MPMSs) based on multicriteria analysis in architectural components. This framework selects the most appropriate system amongst available MPMSs for the telemedicine environment. Prioritisation of MPMSs is a challenging task due to (a) multiple evaluation criteria, (b) importance of criteria, (c) data variation and (d) unmeasurable values. The secondary data presented as the decision evaluation matrix include six systems (namely, Yale-National Aeronautics and Space Administration (NASA), advanced health and disaster aid network, personalised health monitoring, CMS, MobiHealth and NTU) as alternatives and 13 criteria (namely, supported number of sensors, sensor front-end (SFE) communication, SFE to mobile base unit (MBU) communications, display of biosignals on the MBU, storage of biosignals on the MBU, intra-body area network (BAN) communication problems, extra-BAN communication problems, extra-BAN communication technology, extra-BAN communication protocols, back-end system communication technology, intended geographic area of use, end-to-end security and reported trial problems) based on the architectural components of MPMSs. These criteria are adopted from the most relevant studies and are found to be applicable to this study. The prioritisation framework is developed in three stages. (1) The unmeasurable values of the MPMS evaluation criteria in the adopted decision evaluation matrix based on expert opinion are represented by using the best-worst method (BWM). (2) The importance of the evaluation criteria based on the architectural components of the MPMS is determined by using the BWM. (3) The VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method is utilised to rank the MPMSs according to the determined importance of the evaluation criteria and the adopted decision matrix. For validation, mean ± standard deviation is used to verify the similarity of systematic prioritisations objectively. The following results are obtained. (1) The BWM represents the unmeasurable values of the MPMS evaluation criteria. (2) The BWM is suitable for weighing the evaluation criteria based on the architectural components of the MPMS. (3) VIKOR is suitable for solving the MPMS prioritisation problem. Moreover, the internal and external VIKOR group decision making are approximately the same, with the best MPMS being 'Yale-NASA' and the worst MPMS being 'NTU'. (4) For the objective validation, remarkable differences are observed between the group scores, which indicate the similarity of internal and external prioritisation results.
    Matched MeSH terms: Decision Making*
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