Displaying publications 81 - 100 of 313 in total

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  1. Mohd Sani N, Aziz Z, Kamarulzaman A
    Ther Innov Regul Sci, 2021 05;55(3):490-502.
    PMID: 33231863 DOI: 10.1007/s43441-020-00243-y
    INTRODUCTION: Biosimilars are a cost-effective alternative to original biologic medicines that allow patients access to biologic therapies for various chronic diseases. Our paper aims to provide an overview of biosimilars in Malaysia with emphasis on the comparison of Malaysian guidelines with guidelines from well-established regulatory agencies, a review of biosimilars' market approval and their reported adverse effects (AEs) as well as clinical trials conducted in Malaysia.

    METHODS: We searched the official websites of the National Pharmaceutical Regulatory Agency (NPRA) Malaysia and three other well-established agencies, online databases of Medline® and EMBASE for guidelines on legislation and regulations of biosimilars. Meanwhile, we extracted the reports of AEs involving biosimilars in Malaysia from the NPRA database and for global AEs from the World Health Organisation VigyLize database. The ClinicalTrials.gov Website by the U.S. National Library of Medicines was the source for data on clinical trials.

    RESULTS: Malaysia followed the principles of the European Medicines Agency biosimilar regulations and issued their guideline in 2008. Since then, NPRA has approved 24 biosimilar products and recorded 499 AE reports, of which 43 (8.6%) were serious. NPRA has also approved ten Phase III clinical trials in Malaysia with four trials still ongoing.

    CONCLUSION: Malaysia follows a stringent regulatory pathway for the approval of biosimilars enacted by well-established regulatory agencies to maintain the quality, efficacy and safety of biosimilars. Introducing biosimilars to the Malaysian market would improve patients' accessibility to biologic therapies.

    Matched MeSH terms: Databases, Factual
  2. Olakotan OO, Mohd Yusof M
    Health Informatics J, 2021 4 16;27(2):14604582211007536.
    PMID: 33853395 DOI: 10.1177/14604582211007536
    A CDSS generates a high number of inappropriate alerts that interrupt the clinical workflow. As a result, clinicians silence, disable, or ignore alerts, thereby undermining patient safety. Therefore, the effectiveness and appropriateness of CDSS alerts need to be evaluated. A systematic review was carried out to identify the factors that affect CDSS alert appropriateness in supporting clinical workflow. Seven electronic databases (PubMed, Scopus, ACM, Science Direct, IEEE, Ovid Medline, and Ebscohost) were searched for English language articles published between 1997 and 2018. Seventy six papers met the inclusion criteria, of which 26, 24, 15, and 11 papers are retrospective cohort, qualitative, quantitative, and mixed-method studies, respectively. The review highlights various factors influencing the appropriateness and efficiencies of CDSS alerts. These factors are categorized into technology, human, organization, and process aspects using a combination of approaches, including socio-technical framework, five rights of CDSS, and Lean. Most CDSS alerts were not properly designed based on human factor methods and principles, explaining high alert overrides in clinical practices. The identified factors and recommendations from the review may offer valuable insights into how CDSS alerts can be designed appropriately to support clinical workflow.
    Matched MeSH terms: Databases, Factual
  3. Ismail M, Alsalahi A, Aljaberi MA, Ibrahim RM, Bakar FA, Ideris A
    Nutrients, 2021 Mar 23;13(3).
    PMID: 33806762 DOI: 10.3390/nu13031028
    Edible bird's nest (EBN) is constructed from saliva of swiftlets birds and consumed largely by Southeast and East Asians for its nutritional value and anti-aging properties. Although the neuroprotection of EBN in animals has been reported, there has not been yet systemically summarized. Thus, this review systemically outlined the evidence of the neuroprotective activity of EBN in modulating the cognitive functions of either healthy or with induced-cognitive dysfunction animals as compared to placebos. The related records from 2010 to 2020 were retrieved from PubMed, Scopus, Web of Science and ScienceDirect using pre-specified keywords. The relevant records to the effect of EBN on cognition were selected according to the eligibility criteria and these studies underwent appraisal for the risk of bias. EBN improved the cognitive functions of induced-cognitive dysfunction and enhanced the cognitive performance of healthy animals as well as attenuated the neuroinflammations and neuro-oxidative stress in the hippocampus of these animals. Malaysian EBN could improve the cognitive functions of experimental animals as a treatment in induced cognitive dysfunction, a nutritional cognitive-enhancing agent in offspring and a prophylactic conservative effect on cognition against exposure to subsequent noxious cerebral accidents in a dose-depended manner through attenuating neuroinflammation and neuro-oxidative stress. This systemic review did not proceed meta-analysis.
    Matched MeSH terms: Databases, Factual
  4. Lim HM, Teo CH, Ng CJ, Chiew TK, Ng WL, Abdullah A, et al.
    JMIR Med Inform, 2021 Feb 26;9(2):e23427.
    PMID: 33600345 DOI: 10.2196/23427
    BACKGROUND: During the COVID-19 pandemic, there was an urgent need to develop an automated COVID-19 symptom monitoring system to reduce the burden on the health care system and to provide better self-monitoring at home.

    OBJECTIVE: This paper aimed to describe the development process of the COVID-19 Symptom Monitoring System (CoSMoS), which consists of a self-monitoring, algorithm-based Telegram bot and a teleconsultation system. We describe all the essential steps from the clinical perspective and our technical approach in designing, developing, and integrating the system into clinical practice during the COVID-19 pandemic as well as lessons learned from this development process.

    METHODS: CoSMoS was developed in three phases: (1) requirement formation to identify clinical problems and to draft the clinical algorithm, (2) development testing iteration using the agile software development method, and (3) integration into clinical practice to design an effective clinical workflow using repeated simulations and role-playing.

    RESULTS: We completed the development of CoSMoS in 19 days. In Phase 1 (ie, requirement formation), we identified three main functions: a daily automated reminder system for patients to self-check their symptoms, a safe patient risk assessment to guide patients in clinical decision making, and an active telemonitoring system with real-time phone consultations. The system architecture of CoSMoS involved five components: Telegram instant messaging, a clinician dashboard, system administration (ie, back end), a database, and development and operations infrastructure. The integration of CoSMoS into clinical practice involved the consideration of COVID-19 infectivity and patient safety.

    CONCLUSIONS: This study demonstrated that developing a COVID-19 symptom monitoring system within a short time during a pandemic is feasible using the agile development method. Time factors and communication between the technical and clinical teams were the main challenges in the development process. The development process and lessons learned from this study can guide the future development of digital monitoring systems during the next pandemic, especially in developing countries.

    Matched MeSH terms: Databases, Factual
  5. Mohd Kamal DA, Ibrahim SF, Kamal H, Kashim MIAM, Mokhtar MH
    Nutrients, 2021 Jan 10;13(1).
    PMID: 33435215 DOI: 10.3390/nu13010197
    Tualang, Gelam and Kelulut honeys are tropical rainforest honeys reported to have various medicinal properties. Studies related to the medicinal properties and physicochemical characteristics of these honeys are growing extensively and receiving increased attention. This review incorporated and analysed the findings on the biological and physicochemical properties of these honeys. Tualang, Gelam and Kelulut honeys were found to possess a wide variety of biological effects attributed to their physicochemical characteristics. Findings revealed that these honeys have anti-diabetic, anti-obesity, anti-cancer, anti-oxidative, anti-microbial, anti-inflammatory and wound-healing properties and effects on the cardiovascular system, nervous system and reproductive system. The physicochemical properties of these honeys were compared and discussed and results showed that they have high-quality contents and excellent antioxidant sources.
    Matched MeSH terms: Databases, Factual
  6. Ramírez Varela A, Cruz GIN, Hallal P, Blumenberg C, da Silva SG, Salvo D, et al.
    Int J Behav Nutr Phys Act, 2021 01 07;18(1):5.
    PMID: 33413479 DOI: 10.1186/s12966-020-01071-x
    BACKGROUND: National, regional and global scientific production and research capacity for physical activity - PA may contribute to improving public health PA policies and programs. There is an uneven distribution of research productivity by region and country income group, where countries with the highest burden of non-communicable diseases attributable to physical inactivity having low research productivity. A first step towards improving global research capacity is to objectively quantify patterns, trends, and gaps in PA research. This study describes national, regional and global trends and patterns of PA research from 1950 to 2019.

    METHODS: A systematic review using searches in PubMed, SCOPUS and ISI Web of Knowledge databases was conducted in August 2017 and updated between January and May 2020. The review was registered at the PROSPERO database number CRD42017070153. PA publications per 100,000 inhabitants per country was the main variable of interest. Descriptive and time-trend analyses were conducted in STATA version 16.0.

    RESULTS: The search retrieved 555,468 articles of which 75,756 were duplicates, leaving 479,712 eligible articles. After reviewing inclusion and exclusion criteria, 23,860 were eligible for data extraction. Eighty-one percent of countries (n = 176) had at least one PA publication. The overall worldwide publication rate in the PA field was 0.46 articles per 100,000 inhabitants. Europe had the highest rate (1.44 articles per 100,000 inhabitants) and South East Asia had the lowest (0.04 articles per 100,000 inhabitants). A more than a 50-fold difference in publications per 100,000 inhabitants was identified between high and low-income countries. The least productive and poorest regions have rates resembling previous decades of the most productive and the richest.

    CONCLUSION: This study showed an increasing number of publications over the last 60 years with a growing number of disciplines and research methods over time. However, striking inequities were revealed and the knowledge gap across geographic regions and by country income groups was substantial over time. The need for regular global surveillance of PA research, particularly in countries with the largest data gaps is clear. A focus on the public health impact and global equity of research will be an important contribution to making the world more active.

    Matched MeSH terms: Databases, Factual
  7. Baig AM, Khan NA, Katyara P, Lalani S, Baig R, Nadeem M, et al.
    Chem Biol Drug Des, 2021 01;97(1):18-27.
    PMID: 32602961 DOI: 10.1111/cbdd.13755
    Acanthamoeba spp. cause a corneal infection, Acanthamoeba keratitis (AK), and a cerebral infection, granulomatous amoebic encephalitis (GAE). Though aggressive chemotherapy has been able to kill the active trophozoite form of Acanthamoeba, the encysted form of this parasite has remained problematic to resist physiological concentrations of drugs. The emergence of encysted amoeba into active trophozoite form poses a challenge to eradicate this parasite. Acanthamoeba trophozoites have active metabolic machinery that furnishes energy in the form of ATPs by subjecting carbohydrates and lipids to undergo pathways including glycolysis and beta-oxidation of free fatty acids, respectively. However, very little is known about the metabolic preferences and dependencies of an encysted trophozoite on minerals or potential nutrients that it consumes to live in an encysted state. Here, we investigate the metabolic and nutrient preferences of the encysted trophozoite of Acanthamoeba castellanii and the possibility to target them by drugs that act on calcium ion dependencies of the encysted amoeba. The experimental assays, immunostaining coupled with bioinformatics tools show that the encysted Acanthamoeba uses diverse nutrient pathways to obtain energy in the quiescent encysted state. These findings highlight potential pathways that can be targeted in eradicating amoebae cysts successfully.
    Matched MeSH terms: Databases, Factual
  8. Charan J, Kaur RJ, Bhardwaj P, Haque M, Sharma P, Misra S, et al.
    Expert Rev Clin Pharmacol, 2021 Jan;14(1):95-103.
    PMID: 33252992 DOI: 10.1080/17512433.2021.1856655
    Objectives: Remdesivir has shown promise in the management of patients with COVID-19 although recent studies have shown concerns with its effectiveness in practice. Despite this there is a need to document potential adverse drug events (ADEs) to guide future decisions as limited ADE data available before the COVID-19 pandemic. Methods: Interrogation of WHO VigiBase® from 2015 to 2020 coupled with published studies of ADEs in COVID-19 patients. The main outcome measures are the extent of ADEs broken down by factors including age, seriousness, region and organ. Results: A total 1086 ADEs were reported from the 439 individual case reports up to July 19, 2020, in the VigiBase®, reduced to 1004 once duplicates were excluded. Almost all ADEs concerned COVID-19 patients (92.5%), with an appreciable number from the Americas (67.7%). The majority of ADEs were from males > 45 years and were serious (82.5%). An increase in hepatic enzymes (32.1%), renal injury (14.4%), rise in creatinine levels (11.2%), and respiratory failure (6.4%) were the most frequently reported ADEs. Conclusions: Deterioration of liver and kidney function are frequently observed ADEs with remdesivir; consequently, patients should be monitored for these ADEs. The findings are in line with ADEs included in regulatory authority documents.
    Matched MeSH terms: Databases, Factual*
  9. Lee CY, Liu KT, Lu HT, Mohd Ali R, Fong AYY, Wan Ahmad WA
    PLoS One, 2021;16(2):e0246474.
    PMID: 33556136 DOI: 10.1371/journal.pone.0246474
    BACKGROUND: Sex and gender differences in acute coronary syndrome (ACS) have been well studied in the western population. However, limited studies have examined the trends of these differences in a multi-ethnic Asian population.

    OBJECTIVES: To study the trends in sex and gender differences in ACS using the Malaysian NCVD-ACS Registry.

    METHODS: Data from 24 hospitals involving 35,232 ACS patients (79.44% men and 20.56% women) from 1st. Jan 2012 to 31st. Dec 2016 were analysed. Data were collected on demographic characteristics, coronary risk factors, anthropometrics, treatments and outcomes. Analyses were done for ACS as a whole and separately for ST-segment elevation myocardial infarction (STEMI), Non-STEMI and unstable angina. These were then compared to published data from March 2006 to February 2010 which included 13,591 ACS patients (75.8% men and 24.2% women).

    RESULTS: Women were older and more likely to have diabetes mellitus, hypertension, dyslipidemia, previous heart failure and renal failure than men. Women remained less likely to receive aspirin, beta-blocker, angiotensin-converting enzyme inhibitor (ACE-I) and statin. Women were less likely to undergo angiography and percutaneous coronary intervention (PCI) despite an overall increase. In the STEMI cohort, despite a marked increase in presentation with Killip class IV, women were less likely to received primary PCI or fibrinolysis and had longer median door-to-needle and door-to-balloon time compared to men, although these had improved. Women had higher unadjusted in-hospital, 30-Day and 1-year mortality rates compared to men for the STEMI and NSTEMI cohorts. After multivariate adjustments, 1-year mortality remained significantly higher for women with STEMI (adjusted OR: 1.31 (1.09-1.57), p<0.003) but were no longer significant for NSTEMI cohort.

    CONCLUSION: Women continued to have longer system delays, receive less aggressive pharmacotherapies and invasive treatments with poorer outcome. There is an urgent need for increased effort from all stakeholders if we are to narrow this gap.

    Matched MeSH terms: Databases, Factual
  10. Tan KF, Adam F, Hussin H, Mohd Mujar NM
    Epidemiol Health, 2021;43:e2021038.
    PMID: 34044478 DOI: 10.4178/epih.e2021038
    This study compared breast cancer survival and the prognostic factors across different age groups of women in Penang, Malaysia. Data on 2,166 women with breast cancer who had been diagnosed between 2010 and 2014 were extracted from the Penang Breast Cancer Registry and stratified into 3 age groups: young (< 40 years old), middle-aged (40-59 years old), and elderly (≥ 60 years). The overall and relative survival rates were calculated using the life table method, median survival time was calculated using the Kaplan-Meier method, and comparisons between groups were conducted using the log-rank test. Prognostic factors were analyzed using a Cox proportional hazards model. The 5-year overall and breast cancer-specific survival rates for women with breast cancer in Penang were 72.9% and 75.2%, with a mean survival time of 92.5 months and 95.1 months, respectively. The 5-year breast cancer-specific survival rates for young, middle-aged, and elderly women were 74.9%, 77.8%, and 71.4%, respectively, with a mean survival time of 95.7 months, 97.5 months, and 91.2 months. There was a significant difference in breast cancer survival between age groups, with elderly women showing the lowest survival rate, followed by young and middle-aged women. Disease stage was the most prominent prognostic factor for all age groups. Survival rates and prognostic factors differed according to age group. Treatment planning for breast cancer patients should be age-specific to promote better cancer care and survival.
    Matched MeSH terms: Databases, Factual
  11. Alefishat E, Abu Farha R, Zawiah M
    PLoS One, 2021;16(8):e0256031.
    PMID: 34388191 DOI: 10.1371/journal.pone.0256031
    PURPOSE: The credibility and the reliability of Internet webpages to seek medication-related information is questionable. The main objective of the current study was to evaluate perception and experience of pharmacists with the use of Internet-based medication information by their patients.

    METHODS: This is a cross-sectional descriptive study that was conducted to evaluate perception and experience of pharmacists with the use of Internet-based medication information by their patients. During the study period, 200 pharmacists were approached to participate in the study using a paper-based survey to assess their perceptions and current experience with the use of Internet-based medication information by their patients. Data were analyzed using descriptive statistics (mean/standard deviation for continuous variables, and frequency/percentages for qualitative variables). Also, simple linear regression was utilized to screen factors affecting pharmacists' perception scores of the use of Internet-based medication information.

    RESULTS: Among 161 recruited pharmacists, the majority (n = 129, 80.1%) reported receiving inquiries from patients about Internet-based medication information within the last year. Among them, only 22.6% (n = 29) of pharmacists believed that Internet-based medication information is somewhat or very accurate. Unfortunately, only 24.2% (n = 31) of them stated that they always had enough time for their patient to discuss their Internet-based medication information. Regarding pharmacists' perception of the use of Internet-based medication information by their patients, more than half of the pharmacists (>50%) believe that Internet-based medication information could increase the patient's role in taking responsibility. On the other hand, 54.7% (n = 88) of the pharmacists believed that Internet-based medication information would contribute to rising the healthcare cost by obtaining unnecessary medications by patients. Finally, pharmacists' educational level was found to significantly affect their perception scores toward patient use of Internet-based medication information where those with higher educational level showed lower perception score (r = -0.200, P-value = 0.011).

    CONCLUSION: Although pharmacists felt that usage of Internet-based data by patients is beneficial, they also have believed that it has a negative impact in terms of rising the healthcare cost, and it promotes unnecessary fear or concern about medications. We suggest that pharmacists be trained on principles of critical appraisal to become professional in retrieval information on the Internet that might improve their delivery of healthcare information and their recommendations to patients.

    Matched MeSH terms: Databases, Factual
  12. Rehman MZ, Zamli KZ, Almutairi M, Chiroma H, Aamir M, Kader MA, et al.
    PLoS One, 2021;16(12):e0259786.
    PMID: 34855771 DOI: 10.1371/journal.pone.0259786
    Team formation (TF) in social networks exploits graphs (i.e., vertices = experts and edges = skills) to represent a possible collaboration between the experts. These networks lead us towards building cost-effective research teams irrespective of the geolocation of the experts and the size of the dataset. Previously, large datasets were not closely inspected for the large-scale distributions & relationships among the researchers, resulting in the algorithms failing to scale well on the data. Therefore, this paper presents a novel TF algorithm for expert team formation called SSR-TF based on two metrics; communication cost and graph reduction, that will become a basis for future TF's. In SSR-TF, communication cost finds the possibility of collaboration between researchers. The graph reduction scales the large data to only appropriate skills and the experts, resulting in real-time extraction of experts for collaboration. This approach is tested on five organic and benchmark datasets, i.e., UMP, DBLP, ACM, IMDB, and Bibsonomy. The SSR-TF algorithm is able to build cost-effective teams with the most appropriate experts-resulting in the formation of more communicative teams with high expertise levels.
    Matched MeSH terms: Databases, Factual
  13. Karobari MI, Maqbool M, Ahmad P, Abdul MSM, Marya A, Venugopal A, et al.
    Biomed Res Int, 2021;2021:6657167.
    PMID: 34746305 DOI: 10.1155/2021/6657167
    Background: Citation analysis has emerged to play a significant role in recognition of the most useful areas of research. Endodontic microbiology has been a topic of interest for endodontists as well as periodontists and oral surgeons. This bibliometric analysis is aimed at identifying and reporting the characteristics of the top 50 cited articles on endodontic microbiology.

    Methods: The articles were identified through a search on Web of Science (WoS), property of Clarivate Analytics database published on endodontic microbiology. The citation information of the selected articles was recorded. The Journal of Endodontics, International Endodontic Journal, Oral Surgery Oral Medicine Oral Pathology Oral Radiology and Endodontology, Dental Traumatology, and Australian Endodontic Journal were searched in the search title. Descriptive and bivariate analyses were performed using a statistical software package SPSS. Statistical analysis was performed using Shapiro-Wilk, Kruskal-Wallis, Post hoc, Mann-Kendall trend, and Spearman-rank tests.

    Results: The 50 most cited articles were published from 1965 to 2012 with citation count varying from 1065 to 103 times. The total citation counts of articles recorded were 11,525 (WoS), 12,602 (Elseviers' Scopus), and 28,871 (Google Scholar). The most prolific years in terms of publications were 2001, 2002, and 2003, with five publications each, followed by 2005 with four. The year with most citations was 1998, with 1,330 citations, followed by 1965 and 2001, with 1,065 and 1,015 citations, respectively. A total of 136 authors contributed to the top 50 most cited articles with 27 corresponding institutions from 12 different countries. The most common methodological design was in vitro study, followed by clinic-laboratory study, literature review, systematic review and meta-analysis, and animal study.

    Conclusions: The present study provided a detailed list of the top 50 most cited and classic articles on microbiology in endodontics. This will help researchers, students, and clinicians in the field of endodontics as an impressive source of information.

    Matched MeSH terms: Databases, Factual
  14. Harun S, Dorasamy M, Bin Ahmad AA, Yap CS, Harguem S
    F1000Res, 2021;10:1148.
    PMID: 37599674 DOI: 10.12688/f1000research.73347.3
    Background: Enterprise resource planning (ERP) is critical to enhancing the ability to control commercial activities and results in a competitive advantage when combined with an organisation's existing competitive advantages. However, our practise review reveals that end users resist ERP implementation because the resulting changes will alter the current status quo. The implementation of an ERP system in an organisation is complex as it affects multiple areas of the business. Resistance to change is cited as a factor of ERP failure. Methods: In this study, we conducted a systematic literature review using Transfield's five stages and established a conceptual framework for ERP system implementation in science and technology parks (STPs). Articles collected from Emerald, Science Direct, ProQuest and Scopus databases between 1 st June 2021 and 15 th June 2021. Two authors were assigned to check the suitability of the articles in order to avoid risk of bias. Articles were analysed based on components of a research paper and the data was tabulated using MS Excel. Results: Only eight papers (0.011% of all the papers) appeared when we searched for papers related to ERP with a focus on post ERP Implementation, end-user behaviours, organisational performance, and the accelerated SAP (system application and product) methodology. We found that there are hardly any articles on ERP post implementations in STP context particularly based on the evaluation part of accelerated SAP.   Conclusions: Results indicate the lack of studies in this field, particularly those addressing issues related to STP. This study attempted to broaden the understanding of the ERP's effectiveness, particularly in terms of an organisation's operational performance.
    Matched MeSH terms: Databases, Factual
  15. Usman OL, Muniyandi RC, Omar K, Mohamad M
    PLoS One, 2021;16(2):e0245579.
    PMID: 33630876 DOI: 10.1371/journal.pone.0245579
    Achieving biologically interpretable neural-biomarkers and features from neuroimaging datasets is a challenging task in an MRI-based dyslexia study. This challenge becomes more pronounced when the needed MRI datasets are collected from multiple heterogeneous sources with inconsistent scanner settings. This study presents a method of improving the biological interpretation of dyslexia's neural-biomarkers from MRI datasets sourced from publicly available open databases. The proposed system utilized a modified histogram normalization (MHN) method to improve dyslexia neural-biomarker interpretations by mapping the pixels' intensities of low-quality input neuroimages to range between the low-intensity region of interest (ROIlow) and high-intensity region of interest (ROIhigh) of the high-quality image. This was achieved after initial image smoothing using the Gaussian filter method with an isotropic kernel of size 4mm. The performance of the proposed smoothing and normalization methods was evaluated based on three image post-processing experiments: ROI segmentation, gray matter (GM) tissues volume estimations, and deep learning (DL) classifications using Computational Anatomy Toolbox (CAT12) and pre-trained models in a MATLAB working environment. The three experiments were preceded by some pre-processing tasks such as image resizing, labelling, patching, and non-rigid registration. Our results showed that the best smoothing was achieved at a scale value, σ = 1.25 with a 0.9% increment in the peak-signal-to-noise ratio (PSNR). Results from the three image post-processing experiments confirmed the efficacy of the proposed methods. Evidence emanating from our analysis showed that using the proposed MHN and Gaussian smoothing methods can improve comparability of image features and neural-biomarkers of dyslexia with a statistically significantly high disc similarity coefficient (DSC) index, low mean square error (MSE), and improved tissue volume estimations. After 10 repeated 10-fold cross-validation, the highest accuracy achieved by DL models is 94.7% at a 95% confidence interval (CI) level. Finally, our finding confirmed that the proposed MHN method significantly outperformed the normalization method of the state-of-the-art histogram matching.
    Matched MeSH terms: Databases, Factual
  16. Sii CKS, Lee JA, Nah SA
    Pediatr Surg Int, 2020 Dec;36(12):1407-1411.
    PMID: 33068142 DOI: 10.1007/s00383-020-04760-7
    PURPOSE: The COVID-19 pandemic has placed extraordinary demands on healthcare services worldwide. Some have reported increased viral transmission to healthcare workers during aerosol-generating procedures such as intubation. We report our experience with universal preoperative and preprocedural screening for COVID-19 in children requiring general anaesthesia with low risk of having the infection.

    METHODS: This was a data review involving children aged 

    Matched MeSH terms: Databases, Factual
  17. Lee FY, Wong HS, Chan HK, Mohamed Ali N, Abu Hassan MR, Omar H, et al.
    Pharmacoepidemiol Drug Saf, 2020 12;29(12):1669-1679.
    PMID: 33064335 DOI: 10.1002/pds.5153
    PURPOSE: To determine the incidence, demographic profile, background of reporters, causative agents, severity and clinical outcomes of hepatic adverse drug reaction (ADR) reports in Malaysia using the national ADR reporting database.

    METHODS: The ADR reports recorded between 2000 and 2017 were retrospectively analysed to identify hepatic ADR reports. The trend and characteristics of hepatic ADR cases were described. Multivariate disproportionality analysis of the causative agents was performed to generate signals of hepatic ADRs.

    RESULTS: A total of 2090 hepatic ADRs (1.77% of all ADRs) were reported with mortality rate of 12.7% among cases with known clinical outcomes. The incidence of hepatic ADR reporting in Malaysia increased significantly over 18 years from 0.26 to 9.45 per million population (P 

    Matched MeSH terms: Databases, Factual
  18. Md Idris N, Chiam YK, Varathan KD, Wan Ahmad WA, Chee KH, Liew YM
    Med Biol Eng Comput, 2020 Dec;58(12):3123-3140.
    PMID: 33155096 DOI: 10.1007/s11517-020-02268-9
    Coronary artery disease (CAD) is an important cause of mortality across the globe. Early risk prediction of CAD would be able to reduce the death rate by allowing early and targeted treatments. In healthcare, some studies applied data mining techniques and machine learning algorithms on the risk prediction of CAD using patient data collected by hospitals and medical centers. However, most of these studies used all the attributes in the datasets which might reduce the performance of prediction models due to data redundancy. The objective of this research is to identify significant features to build models for predicting the risk level of patients with CAD. In this research, significant features were selected using three methods (i.e., Chi-squared test, recursive feature elimination, and Embedded Decision Tree). Synthetic Minority Over-sampling Technique (SMOTE) oversampling technique was implemented to address the imbalanced dataset issue. The prediction models were built based on the identified significant features and eight machine learning algorithms, utilizing Acute Coronary Syndrome (ACS) datasets provided by National Cardiovascular Disease Database (NCVD) Malaysia. The prediction models were evaluated and compared using six performance evaluation metrics, and the top-performing models have achieved AUC more than 90%. Graphical abstract.
    Matched MeSH terms: Databases, Factual
  19. 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: Databases, Factual
  20. Md Noh MF, Gunasegavan RD, Mustafa Khalid N, Balasubramaniam V, Mustar S, Abd Rashed A
    Molecules, 2020 Oct 06;25(19).
    PMID: 33036314 DOI: 10.3390/molecules25194567
    Food composition database (FCD) provides the nutritional composition of foods. Reliable and up-to date FCD is important in many aspects of nutrition, dietetics, health, food science, biodiversity, plant breeding, food industry, trade and food regulation. FCD has been used extensively in nutrition labelling, nutritional analysis, research, regulation, national food and nutrition policy. The choice of method for the analysis of samples for FCD often depends on detection capability, along with ease of use, speed of analysis and low cost. Sample preparation is the most critical stage in analytical method development. Samples can be prepared using numerous techniques; however it should be applicable for a wide range of analytes and sample matrices. There are quite a number of significant improvements on sample preparation techniques in various food matrices for specific analytes highlighted in the literatures. Improvements on the technology used for the analysis of samples by specific instrumentation could provide an alternative to the analyst to choose for their laboratory requirement. This review provides the reader with an overview of recent techniques that can be used for sample preparation and instrumentation for food analysis which can provide wide options to the analysts in providing data to their FCD.
    Matched MeSH terms: Databases, Factual*
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