Displaying publications 61 - 80 of 312 in total

Abstract:
Sort:
  1. Ganesan K, Acharya RU, Chua CK, Laude A
    Proc Inst Mech Eng H, 2014 Sep;228(9):962-70.
    PMID: 25234036 DOI: 10.1177/0954411914550847
    Identification of retinal landmarks is an important step in the extraction of anomalies in retinal fundus images. In the current study, we propose a technique to identify and localize the position of macula and hence the fovea avascular zone, in colour fundus images. The proposed method, based on varying blur scales in images, is independent of the location of other anatomical landmarks present in the fundus images. Experimental results have been provided using the open database MESSIDOR by validating our segmented regions using the dice coefficient, with ground truth segmentation provided by a human expert. Apart from testing the images on the entire MESSIDOR database, the proposed technique was also validated using 50 normal and 50 diabetic retinopathy chosen digital fundus images from the same database. A maximum overlap accuracy of 89.6%-93.8% and locational accuracy of 94.7%-98.9% was obtained for identification and localization of the fovea.
    Matched MeSH terms: Databases, Factual
  2. Cros A, Ahamad Fatan N, White A, Teoh SJ, Tan S, Handayani C, et al.
    PLoS One, 2014;9(6):e96332.
    PMID: 24941442 DOI: 10.1371/journal.pone.0096332
    In this paper we describe the construction of an online GIS database system, hosted by WorldFish, which stores bio-physical, ecological and socio-economic data for the 'Coral Triangle Area' in South-east Asia and the Pacific. The database has been built in partnership with all six (Timor-Leste, Malaysia, Indonesia, The Philippines, Solomon Islands and Papua New Guinea) of the Coral Triangle countries, and represents a valuable source of information for natural resource managers at the regional scale. Its utility is demonstrated using biophysical data, data summarising marine habitats, and data describing the extent of marine protected areas in the region.
    Matched MeSH terms: Databases, Factual*
  3. Kanapathipillai R, McManus H, Kamarulzaman A, Lim PL, Templeton DJ, Law M, et al.
    PLoS One, 2014;9(2):e86122.
    PMID: 24516527 DOI: 10.1371/journal.pone.0086122
    INTRODUCTION: Magnitude and frequency of HIV viral load blips in resource-limited settings, has not previously been assessed. This study was undertaken in a cohort from a high income country (Australia) known as AHOD (Australian HIV Observational Database) and another cohort from a mixture of Asian countries of varying national income per capita, TAHOD (TREAT Asia HIV Observational Database).

    METHODS: Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.

    RESULTS: 5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.

    CONCLUSION: Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips.

    Matched MeSH terms: Databases, Factual
  4. Mustafa MB, Salim SS, Mohamed N, Al-Qatab B, Siong CE
    PLoS One, 2014;9(1):e86285.
    PMID: 24466004 DOI: 10.1371/journal.pone.0086285
    Automatic speech recognition (ASR) is currently used in many assistive technologies, such as helping individuals with speech impairment in their communication ability. One challenge in ASR for speech-impaired individuals is the difficulty in obtaining a good speech database of impaired speakers for building an effective speech acoustic model. Because there are very few existing databases of impaired speech, which are also limited in size, the obvious solution to build a speech acoustic model of impaired speech is by employing adaptation techniques. However, issues that have not been addressed in existing studies in the area of adaptation for speech impairment are as follows: (1) identifying the most effective adaptation technique for impaired speech; and (2) the use of suitable source models to build an effective impaired-speech acoustic model. This research investigates the above-mentioned two issues on dysarthria, a type of speech impairment affecting millions of people. We applied both unimpaired and impaired speech as the source model with well-known adaptation techniques like the maximum likelihood linear regression (MLLR) and the constrained-MLLR(C-MLLR). The recognition accuracy of each impaired speech acoustic model is measured in terms of word error rate (WER), with further assessments, including phoneme insertion, substitution and deletion rates. Unimpaired speech when combined with limited high-quality speech-impaired data improves performance of ASR systems in recognising severely impaired dysarthric speech. The C-MLLR adaptation technique was also found to be better than MLLR in recognising mildly and moderately impaired speech based on the statistical analysis of the WER. It was found that phoneme substitution was the biggest contributing factor in WER in dysarthric speech for all levels of severity. The results show that the speech acoustic models derived from suitable adaptation techniques improve the performance of ASR systems in recognising impaired speech with limited adaptation data.
    Matched MeSH terms: Databases, Factual
  5. Saokaew S, Sugimoto T, Kamae I, Pratoomsoot C, Chaiyakunapruk N
    PLoS One, 2015;10(11):e0141993.
    PMID: 26560127 DOI: 10.1371/journal.pone.0141993
    Health technology assessment (HTA) has been continuously used for value-based healthcare decisions over the last decade. Healthcare databases represent an important source of information for HTA, which has seen a surge in use in Western countries. Although HTA agencies have been established in Asia-Pacific region, application and understanding of healthcare databases for HTA is rather limited. Thus, we reviewed existing databases to assess their potential for HTA in Thailand where HTA has been used officially and Japan where HTA is going to be officially introduced.
    Matched MeSH terms: Databases, Factual/statistics & numerical data*
  6. Ngamwong Y, Tangamornsuksan W, Lohitnavy O, Chaiyakunapruk N, Scholfield CN, Reisfeld B, et al.
    PLoS One, 2015;10(8):e0135798.
    PMID: 26274395 DOI: 10.1371/journal.pone.0135798
    Smoking and asbestos exposure are important risks for lung cancer. Several epidemiological studies have linked asbestos exposure and smoking to lung cancer. To reconcile and unify these results, we conducted a systematic review and meta-analysis to provide a quantitative estimate of the increased risk of lung cancer associated with asbestos exposure and cigarette smoking and to classify their interaction. Five electronic databases were searched from inception to May, 2015 for observational studies on lung cancer. All case-control (N = 10) and cohort (N = 7) studies were included in the analysis. We calculated pooled odds ratios (ORs), relative risks (RRs) and 95% confidence intervals (CIs) using a random-effects model for the association of asbestos exposure and smoking with lung cancer. Lung cancer patients who were not exposed to asbestos and non-smoking (A-S-) were compared with; (i) asbestos-exposed and non-smoking (A+S-), (ii) non-exposure to asbestos and smoking (A-S+), and (iii) asbestos-exposed and smoking (A+S+). Our meta-analysis showed a significant difference in risk of developing lung cancer among asbestos exposed and/or smoking workers compared to controls (A-S-), odds ratios for the disease (95% CI) were (i) 1.70 (A+S-, 1.31-2.21), (ii) 5.65; (A-S+, 3.38-9.42), (iii) 8.70 (A+S+, 5.8-13.10). The additive interaction index of synergy was 1.44 (95% CI = 1.26-1.77) and the multiplicative index = 0.91 (95% CI = 0.63-1.30). Corresponding values for cohort studies were 1.11 (95% CI = 1.00-1.28) and 0.51 (95% CI = 0.31-0.85). Our results point to an additive synergism for lung cancer with co-exposure of asbestos and cigarette smoking. Assessments of industrial health risks should take smoking and other airborne health risks when setting occupational asbestos exposure limits.
    Matched MeSH terms: Databases, Factual*
  7. Ong HC, Alih E
    PLoS One, 2015;10(4):e0125835.
    PMID: 25923739 DOI: 10.1371/journal.pone.0125835
    The tendency for experimental and industrial variables to include a certain proportion of outliers has become a rule rather than an exception. These clusters of outliers, if left undetected, have the capability to distort the mean and the covariance matrix of the Hotelling's T2 multivariate control charts constructed to monitor individual quality characteristics. The effect of this distortion is that the control chart constructed from it becomes unreliable as it exhibits masking and swamping, a phenomenon in which an out-of-control process is erroneously declared as an in-control process or an in-control process is erroneously declared as out-of-control process. To handle these problems, this article proposes a control chart that is based on cluster-regression adjustment for retrospective monitoring of individual quality characteristics in a multivariate setting. The performance of the proposed method is investigated through Monte Carlo simulation experiments and historical datasets. Results obtained indicate that the proposed method is an improvement over the state-of-art methods in terms of outlier detection as well as keeping masking and swamping rate under control.
    Matched MeSH terms: Databases, Factual*
  8. 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
  9. Mujtaba G, Shuib L, Raj RG, Rajandram R, Shaikh K, Al-Garadi MA
    PLoS One, 2017;12(2):e0170242.
    PMID: 28166263 DOI: 10.1371/journal.pone.0170242
    OBJECTIVES: Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. Numerous machine learning techniques, such as supervised machine learning approaches or ontology-based approaches, have been employed to obtain useful information from plaintext clinical data. This study proposes an automatic multi-class classification system to predict accident-related causes of death from plaintext autopsy reports through expert-driven feature selection with supervised automatic text classification decision models.

    METHODS: Accident-related autopsy reports were obtained from one of the largest hospital in Kuala Lumpur. These reports belong to nine different accident-related causes of death. Master feature vector was prepared by extracting features from the collected autopsy reports by using unigram with lexical categorization. This master feature vector was used to detect cause of death [according to internal classification of disease version 10 (ICD-10) classification system] through five automated feature selection schemes, proposed expert-driven approach, five subset sizes of features, and five machine learning classifiers. Model performance was evaluated using precisionM, recallM, F-measureM, accuracy, and area under ROC curve. Four baselines were used to compare the results with the proposed system.

    RESULTS: Random forest and J48 decision models parameterized using expert-driven feature selection yielded the highest evaluation measure approaching (85% to 90%) for most metrics by using a feature subset size of 30. The proposed system also showed approximately 14% to 16% improvement in the overall accuracy compared with the existing techniques and four baselines.

    CONCLUSION: The proposed system is feasible and practical to use for automatic classification of ICD-10-related cause of death from autopsy reports. The proposed system assists pathologists to accurately and rapidly determine underlying cause of death based on autopsy findings. Furthermore, the proposed expert-driven feature selection approach and the findings are generally applicable to other kinds of plaintext clinical reports.

    Matched MeSH terms: Databases, Factual
  10. 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
  11. 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
  12. Al-Dhaqm A, Razak S, Othman SH, Ngadi A, Ahmed MN, Ali Mohammed A
    PLoS One, 2017;12(2):e0170793.
    PMID: 28146585 DOI: 10.1371/journal.pone.0170793
    Database Forensics (DBF) is a widespread area of knowledge. It has many complex features and is well known amongst database investigators and practitioners. Several models and frameworks have been created specifically to allow knowledge-sharing and effective DBF activities. However, these are often narrow in focus and address specified database incident types. We have analysed 60 such models in an attempt to uncover how numerous DBF activities are really public even when the actions vary. We then generate a unified abstract view of DBF in the form of a metamodel. We identified, extracted, and proposed a common concept and reconciled concept definitions to propose a metamodel. We have applied a metamodelling process to guarantee that this metamodel is comprehensive and consistent.
    Matched MeSH terms: Databases, Factual*
  13. Thai YC, Sim D, McCaffrey TA, Ramadas A, Malini H, Watterson JL
    PLoS One, 2023;18(2):e0282118.
    PMID: 36854022 DOI: 10.1371/journal.pone.0282118
    INTRODUCTION: Digital technology-based interventions have gained popularity over the last two decades, due to the ease with which they are scalable and low in implementation cost. Multicomponent health promotion programmes, with significant digital components, are increasingly being deployed in the workplace to assess and promote employees' health behaviours and reduce risk of chronic diseases. However, little is known about workplace digital health interventions in low- and middle- income countries (LMICs).

    METHODS: Various combinations of keywords related to "digital health", "intervention", "workplace" and "developing country" were applied in Ovid MEDLINE, EMBASE, CINAHL Plus, PsycINFO, Scopus and Cochrane Library for peer-reviewed articles in English language. Manual searches were performed to supplement the database search. The screening process was conducted in two phases and a narrative synthesis to summarise the data. The review protocol was written prior to undertaking the review (OSF Registry:10.17605/OSF.IO/QPR9J).

    RESULTS: The search strategy identified 10,298 publications, of which 24 were included. Included studies employed the following study designs: randomized-controlled trials (RCTs) (n = 12), quasi-experimental (n = 4), pilot studies (n = 4), pre-post studies (n = 2) and cohort studies (n = 2). Most of the studies reported positive feedback of the use of digital wellness interventions in workplace settings.

    CONCLUSIONS: This review is the first to map and describe the impact of digital wellness interventions in the workplace in LMICs. Only a small number of studies met the inclusion criteria. Modest evidence was found that digital workplace wellness interventions were feasible, cost-effective, and acceptable. However, long-term, and consistent effects were not found, and further studies are needed to provide more evidence. This scoping review identified multiple digital health interventions in LMIC workplace settings and highlighted a few important research gaps.

    Matched MeSH terms: Databases, Factual
  14. Md Zamri ASS, Saruddin MZ, Harun A, Abd Aziz SF, Aizad Za'bah AK, Dapari R, et al.
    PLoS One, 2023;18(6):e0287040.
    PMID: 37307252 DOI: 10.1371/journal.pone.0287040
    INTRODUCTION: Occupational asthma (OA) is a type of Work-Related Asthma characterised by variable airflow limitation and/or inflammation due to causes and conditions attributable to a particular occupational environment, and not to stimuli encountered outside the workplace. There is an increasing need to extend the depth of knowledge of OA to better manage this condition, especially among food industry workers who are affected by it.

    OBJECTIVE: This systematic review aimed to determine the factors associated with occupational asthma among food industry workers by electronically collecting articles from two databases (Medline and Scopus).

    METHODS: This systematic review was prepared in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta Analyses) updated guideline. Two independent reviewers screened the titles and abstracts of the collected data, which were then stored in Endnote20 based on the inclusion and exclusion criteria. The included articles have been critically appraised to assess the quality of the studies using the Mixed Methods Appraisal Tool (MMAT).

    RESULT: The search yielded 82 articles from Medline and 85 from SCOPUS, resulting in 167 unique hits. Only 22 articles have been included in the full-text assessment following a rigorous selection screening. Of the 22 articles identified, five were included in the final review. Several factors were found to have contributed to occupational asthma among food industry workers. They were classified into two categories: (1) work environment-related factors; and (2) individual factors.

    CONCLUSION: Several work environment and individual-related factors were found to be associated with OA among food industry workers. A better understanding of the development of the disease and its potential risk factors is needed because it can affect worker's quality of life. Pre-employment and periodic medical surveillance should be conducted to assess and detect any possible risk of developing occupational asthma among workers.

    Matched MeSH terms: Databases, Factual
  15. Loh ZC, Hussain R, Balan S, Saini B, Muneswarao J, Ong SC, et al.
    PLoS One, 2023;18(4):e0283876.
    PMID: 37079594 DOI: 10.1371/journal.pone.0283876
    BACKGROUND: Short-acting β2-agonists (SABA), the most potent and rapid-acting relievers are commonly used to provide quick relief of asthma symptoms. However, there is an increasing concern regarding the misuse of SABA medicines.

    OBJECTIVE: This qualitative systematic review aims to determine, evaluate, and summarize the perceptions, attitudes, and behaviors towards the use of SABA from the patients' perspectives.

    METHODS: The databases searched included PubMed, Scopus, PsycINFO, CINAHL, and Cochrane database. Original research articles reporting the perceptions, attitudes, or behaviors of asthma patients towards the use of SABA, which was available as full text, published in the English language between the year 2000 and February 2023 were included in the review. Commentaries, letters to editor, review articles, and conference proceedings were excluded.

    RESULTS: A total of five articles were included. Six overarching themes were obtained: (1) perceptions on health status; (2) perceptions and attitudes towards the impact of asthma; (3) perceptions towards asthma control; (4) perceptions towards asthma knowledge; (5) risk perceptions; (6) perceptions, attitudes, and behaviors towards the use of SABA.

    CONCLUSION: Despite the fact that SABA could rapidly alleviate asthma symptoms, SABA over-users were less likely to describe their health status and asthma control as 'excellent'. Most SABA over-users did not know that frequent SABA usage would worsen their asthma control, and they exhibited psychological linkage towards the use of SABA. Collaborative efforts between policymakers, healthcare professionals and patients are warranted to reconstruct SABA prescribing practice and usage.

    Matched MeSH terms: Databases, Factual
  16. Billah MA, Miah MM, Khan MN
    PLoS One, 2020;15(11):e0242128.
    PMID: 33175914 DOI: 10.1371/journal.pone.0242128
    BACKGROUND: The coronavirus (SARS-COV-2) is now a global concern because of its higher transmission capacity and associated adverse consequences including death. The reproductive number of coronavirus provides an estimate of the possible extent of the transmission. This study aims to provide a summary reproductive number of coronavirus based on available global level evidence.

    METHODS: A total of three databases were searched on September 15, 2020: PubMed, Web of Science, and Science Direct. The searches were conducted using a pre-specified search strategy to record studies reported the reproductive number of coronavirus from its inception in December 2019. It includes keywords of coronavirus and its reproductive number, which were combined using the Boolean operators (AND, OR). Based on the included studies, we estimated a summary reproductive number by using the meta-analysis. We used narrative synthesis to explain the results of the studies where the reproductive number was reported, however, were not possible to include in the meta-analysis because of the lack of data (mostly due to confidence interval was not reported).

    RESULTS: Total of 42 studies included in this review whereas 29 of them were included in the meta-analysis. The estimated summary reproductive number was 2.87 (95% CI, 2.39-3.44). We found evidence of very high heterogeneity (99.5%) of the reproductive number reported in the included studies. Our sub-group analysis was found the significant variations of reproductive number across the country for which it was estimated, method and model that were used to estimate the reproductive number, number of case that was considered to estimate the reproductive number, and the type of reproductive number that was estimated. The highest reproductive number was reported for the Diamond Princess Cruise Ship in Japan (14.8). In the country-level, the higher reproductive number was reported for France (R, 6.32, 95% CI, 5.72-6.99) following Germany (R, 6.07, 95% CI, 5.51-6.69) and Spain (R, 3.56, 95% CI, 1.62-7.82). The higher reproductive number was reported if it was estimated by using the Markov Chain Monte Carlo method (MCMC) method and the Epidemic curve model. We also reported significant heterogeneity of the type of reproductive number- a high-value reported if it was the time-dependent reproductive number.

    CONCLUSION: The estimated summary reproductive number indicates an exponential increase of coronavirus infection in the coming days. Comprehensive policies and programs are important to reduce new infections as well as the associated adverse consequences including death.

    Matched MeSH terms: Databases, Factual
  17. Afolabi LT, Saeed F, Hashim H, Petinrin OO
    PLoS One, 2018;13(1):e0189538.
    PMID: 29329334 DOI: 10.1371/journal.pone.0189538
    Pharmacologically active molecules can provide remedies for a range of different illnesses and infections. Therefore, the search for such bioactive molecules has been an enduring mission. As such, there is a need to employ a more suitable, reliable, and robust classification method for enhancing the prediction of the existence of new bioactive molecules. In this paper, we adopt a recently developed combination of different boosting methods (Adaboost) for the prediction of new bioactive molecules. We conducted the research experiments utilizing the widely used MDL Drug Data Report (MDDR) database. The proposed boosting method generated better results than other machine learning methods. This finding suggests that the method is suitable for inclusion among the in silico tools for use in cheminformatics, computational chemistry and molecular biology.
    Matched MeSH terms: Databases, Factual
  18. Aqra I, Herawan T, Abdul Ghani N, Akhunzada A, Ali A, Bin Razali R, et al.
    PLoS One, 2018;13(1):e0179703.
    PMID: 29351287 DOI: 10.1371/journal.pone.0179703
    Designing an efficient association rule mining (ARM) algorithm for multilevel knowledge-based transactional databases that is appropriate for real-world deployments is of paramount concern. However, dynamic decision making that needs to modify the threshold either to minimize or maximize the output knowledge certainly necessitates the extant state-of-the-art algorithms to rescan the entire database. Subsequently, the process incurs heavy computation cost and is not feasible for real-time applications. The paper addresses efficiently the problem of threshold dynamic updation for a given purpose. The paper contributes by presenting a novel ARM approach that creates an intermediate itemset and applies a threshold to extract categorical frequent itemsets with diverse threshold values. Thus, improving the overall efficiency as we no longer needs to scan the whole database. After the entire itemset is built, we are able to obtain real support without the need of rebuilding the itemset (e.g. Itemset list is intersected to obtain the actual support). Moreover, the algorithm supports to extract many frequent itemsets according to a pre-determined minimum support with an independent purpose. Additionally, the experimental results of our proposed approach demonstrate the capability to be deployed in any mining system in a fully parallel mode; consequently, increasing the efficiency of the real-time association rules discovery process. The proposed approach outperforms the extant state-of-the-art and shows promising results that reduce computation cost, increase accuracy, and produce all possible itemsets.
    Matched MeSH terms: Databases, Factual
  19. Tanuma J, Jiamsakul A, Makane A, Avihingsanon A, Ng OT, Kiertiburanakul S, et al.
    PLoS One, 2016;11(8):e0161562.
    PMID: 27560968 DOI: 10.1371/journal.pone.0161562
    BACKGROUND: In resource-limited settings, routine monitoring of renal function during antiretroviral therapy (ART) has not been recommended. However, concerns for tenofovir disoproxil fumarate (TDF)-related nephrotoxicity persist with increased use.

    METHODS: We investigated serum creatinine (S-Cr) monitoring rates before and during ART and the incidence and prevalence of renal dysfunction after starting TDF by using data from a regional cohort of HIV-infected individuals in the Asia-Pacific. Time to renal dysfunction was defined as time from TDF initiation to the decline in estimated glomerular filtration rate (eGFR) to <60 ml/min/1.73m2 with >30% reduction from baseline using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation or the decision to stop TDF for reported TDF-nephrotoxicity. Predictors of S-Cr monitoring rates were assessed by Poisson regression and risk factors for developing renal dysfunction were assessed by Cox regression.

    RESULTS: Among 2,425 patients who received TDF, S-Cr monitoring rates increased from 1.01 to 1.84 per person per year after starting TDF (incidence rate ratio 1.68, 95%CI 1.62-1.74, p <0.001). Renal dysfunction on TDF occurred in 103 patients over 5,368 person-years of TDF use (4.2%; incidence 1.75 per 100 person-years). Risk factors for developing renal dysfunction included older age (>50 vs. ≤30, hazard ratio [HR] 5.39, 95%CI 2.52-11.50, p <0.001; and using PI-based regimen (HR 1.93, 95%CI 1.22-3.07, p = 0.005). Having an eGFR prior to TDF (pre-TDF eGFR) of ≥60 ml/min/1.73m2 showed a protective effect (HR 0.38, 95%CI, 0.17-0.85, p = 0.018).

    CONCLUSIONS: Renal dysfunction on commencing TDF use was not common, however, older age, lower baseline eGFR and PI-based ART were associated with higher risk of renal dysfunction during TDF use in adult HIV-infected individuals in the Asia-Pacific region.

    Matched MeSH terms: Databases, Factual
  20. 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
Filters
Contact Us

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

External Links