Displaying publications 1 - 20 of 560 in total

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  1. Nayan NA, Ab Hamid H, Suboh MZ, Abdullah N, Jaafar R, Mhd Yusof NA, et al.
    DOI: 10.3991/ijoe.v16i07.13569
    Cardiovascular disease (CVD) is the leading cause of deaths worldwide. In 2017, CVD contributed to 13,503 deaths in Malaysia. The current approaches for CVD prediction are usually invasive and costly. Machine learning (ML) techniques allow an accurate prediction by utilizing the complex interactions among relevant risk factors. This study presents a case–control study involving 60 participants from The Malaysian Cohort, which is a prospective population-based project. Five parameters, namely, the R–R interval and root mean square of successive differences extracted from electrocardiogram (ECG), systolic and diastolic blood pressures, and total cholesterol level, were statistically significant in predicting CVD. Six ML algorithms, namely, linear discriminant analysis, linear and quadratic support vector machines, decision tree, knearest neighbor, and artificial neural network (ANN), were evaluated to determine the most accurate classifier in predicting CVD risk. ANN, which achieved 90% specificity, 90% sensitivity, and 90% accuracy, demonstrated the highest prediction performance among the six algorithms. In summary, by utilizing ML techniques, ECG data can serve as a good parameter for CVD prediction among the Malaysian multiethnic population.
    Keywords—CVD, ECG, machine learning, The Malaysian Cohort, RMSSD
    Study name: The Malaysian Cohort (TMC) project
    Matched MeSH terms: Cardiovascular Diseases
  2. Mohamed W, Ishak KN, Baharum N, Zainudin N, Lim HY, Noh M, et al.
    Adipocyte, 2024 Dec;13(1):2314032.
    PMID: 38373876 DOI: 10.1080/21623945.2024.2314032
    Excessive deposit of epicardial adipose tissue (EAT) were recently shown to be positively correlated with cardiovascular disease (CVD). This study aims to investigate the thickness of EAT and its association with the components of metabolic syndrome among multi-ethnic Malaysians with and without acute coronary syndrome (ACS). A total of 213 patients were recruited, with the thickness of EAT were quantified non-invasively using standard two-dimensional echocardiography. EAT thickness among the Malaysian population was prompted by several demographic factors and medical comorbidities, particularly T2DM and dyslipidaemia. ACS patients have significantly thicker EAT compared to those without ACS (4.1 mm vs 3.7 mm, p = 0.035). Interestingly, among all the races, Chinese had the thickest EAT distribution (4.6 mm vs 3.8 mm), with age (p = 0.04 vs p cardiovascular risk marker among Malaysians with ACS.
    Matched MeSH terms: Cardiovascular Diseases*
  3. Nor Hasliza Mat Desa, Maznah Mat Kasim, Abdul Aziz Jemain
    Sains Malaysiana, 2015;44:239-247.
    The issue of age difference in hospital admission should be given special attention since it affects the structure of hospital care and treatments. Patients of different age groups should be given different priority in service provision. Due to crucial time and limited resources, healthcare managers need to make wise decisions in identifying priorities in age of admission. This paper aimed to propose a construction of a daily composite hospital admission index (CHAI) as an indicator that captures relevant information about the overall performance of hospital admission over time. It involves five different age groups of total patients admitted to seven major public hospitals in the Klang Valley, Malaysia for respiratory and cardiovascular diseases for a period of three years, 2008 - 2010. The criteria weights were predetermined by aggregating the subjective weight based on rank ordered centroid (ROC) method and objective weight based on entropy - kernel method. The highest and lowest scores of CHAI were marked, while the groups of patients were prioritized according to the criteria weight ranking orders.
    Matched MeSH terms: Cardiovascular Diseases
  4. Purwanto, Eswaran C, Logeswaran R, Abdul Rahman AR
    J Med Syst, 2012 Apr;36(2):521-31.
    PMID: 22675726
    Cardiovascular disease (CVD) is the major cause of death globally. More people die of CVDs each year than from any other disease. Over 80% of CVD deaths occur in low and middle income countries and occur almost equally in male and female. In this paper, different computational models based on Bayesian Networks, Multilayer Perceptron,Radial Basis Function and Logistic Regression methods are presented to predict early risk detection of the cardiovascular event. A total of 929 (626 male and 303 female) heart attack data are used to construct the models.The models are tested using combined as well as separate male and female data. Among the models used, it is found that the Multilayer Perceptron model yields the best accuracy result.
    Matched MeSH terms: Cardiovascular Diseases/diagnosis; Cardiovascular Diseases/epidemiology
  5. Lim TO, Ngah BA, Suppiah A, Ismail F, Abdul Rahman R
    Singapore Med J, 1991 Aug;32(4):245-8.
    PMID: 1776003
    Consecutive hypertensives admitted with cardiovascular complications were studied. One hundred and eight complicated hypertensives (10%) out of 1,066 medical admissions were seen in the three month study. Thirty three per cent had cerebrovascular disease, 30% ischaemic heart disease, 2% had malignant hypertension and 85% had hypertensive heart disease. All patients had uncontrolled hypertension at admission (mean blood pressure 184/115 mmHg). Twenty-four patients (22%) were newly diagnosed; of the rest of previously diagnosed hypertensives (78%), 3% had never been on treatment and 56% had dropped out of treatment, which explained their ineffective blood pressure control. However, 18% of patients had apparently been on regular follow up and treatment, and yet their blood pressure control was poor. Many patients had evidence of renal disease. The prevalence of cardiovascular risk factors was also high; 56% had hypercholesterolaemia; 46% had hypertriglyceridaemia; 44% smoked, 38% were overweight or obese, and 18% were diabetic. This indicates that hypertension is best regarded as an ingredient of a cardiovascular risk profile and its management requires multifactorial correction of all risk factors identified.
    Matched MeSH terms: Cardiovascular Diseases/complications*
  6. Lim J, Bhoo-Pathy N, Sothilingam S, Malek R, Sundram M, Tan GH, et al.
    PLoS One, 2015;10(6):e0130820.
    PMID: 26098884 DOI: 10.1371/journal.pone.0130820
    To determine the lower urinary tract symptoms (LUTS) profile and factors affecting its degree of severity including cardiovascular risk profile, age, ethnicity, education level and prostate volume in a multiethnic Asian setting.
    Matched MeSH terms: Cardiovascular Diseases/pathology*
  7. Habizal NH, Abdul Halim S, Bhaskar S, Wan Bebakar WM, Abdullah JM
    Malays J Med Sci, 2015 Jan-Feb;22(1):50-7.
    PMID: 25892950 MyJurnal
    BACKGROUND: Aspirin resistance has posed a major dilemma in the prevention of cardiovascular disease and stroke. There have been many factors that have been associated with aspirin resistance. Among these factors, the inflammatory processes of diabetes and glycaemic control have been significantly associated with aspirin resistance. Our study evaluated the prevalence of aspirin resistance and its associated factors.
    METHODS: This was a cross-sectional, interventional study, which was implemented from October to November 2012 at the Hospital Universiti Sains Malaysia (HUSM). Sixty-nine patients with diabetes who were taking aspirin were enrolled. The glycosylated haemoglobin (HbA1c) and C-reactive protein (CRP) levels were measured in these patients. The thromboelastography (TEG) level was measured using a TEG machine by a trained technician employing standard methods. The variables obtained were analysed for prevalence of aspirin resistance, HbA1c, CRP, and TEG level. The Chi-square test (and Fisher exact test where applicable) were used to evaluate the associations between aspirin resistance with glycaemic control (HbA1c) and inflammatory markers (CRP).
    RESULTS: The prevalence of aspirin resistance was 17.4% (95%; CI 9.3, 28.4). Glycaemic control (HbA1c) and inflammatory markers (CRP) were not associated with aspirin resistance. Aspirin resistance was prevalent in our study population and was comparable to other studies. The mean HbA1c in the aspirin-resistant group was 8.9%, whereas the mean HbA1c in the aspirin-sensitive group was 8.6%.
    CONCLUSION: There was no significant difference in HbA1c between the two groups. There was no significant association between CRP levels and aspirin resistance.
    KEYWORDS: aspirin resistance; diabetes mellitus; thromboelastography
    Study site: NeuroMedical Specialist Clinic, Hospital Universiti Sains Malaysia (HUSM), Kelantan, Malaysia
    Matched MeSH terms: Cardiovascular Diseases
  8. Rezayi M, Farjami Z, Hosseini ZS, Ebrahimi N, Abouzari-Lotf E
    Curr Pharm Des, 2018;24(39):4675-4680.
    PMID: 30636591 DOI: 10.2174/1381612825666190111144525
    Small noncoding microRNAs (miRNAs) are known as noninvasive biomarkers for early detection in various cancers. In fact, miRNAs have key roles in carcinogenicity process such as proliferation, apoptosis and metastasis. After cardiovascular disease, cancer is the second cause of death in the world with an estimated 9.6 million deaths in 2018. So, early diagnosis of cancer is critical for successful treatment. To date, several selective and sensitive laboratory-based methods have been applied for the detection of circulating miRNA, but a simple, short assay time and low-cost method such as a biosensor method as an alternative approach to monitor cancer biomarker is required. In this review, we have highlighted recent advances in biosensors for circulating miRNA detection.
    Matched MeSH terms: Cardiovascular Diseases/blood; Cardiovascular Diseases/diagnosis
  9. Xin LZ, Govindasamy V, Musa S, Abu Kasim NH
    Med Hypotheses, 2013 Oct;81(4):704-6.
    PMID: 23932760 DOI: 10.1016/j.mehy.2013.07.032
    Dental tissues contains stem cells or progenitors that have high proliferative capacity, are clonogenic in vitro and demonstrate the ability to differentiate to multiple type cells involving neurons, bone, cartilage, fat and smooth muscle. Numerous experiments have demonstrated that the multipotent stem cells are not rejected by immune system and therefore it may be possible to use these cells in allogeneic settings. In addition, these remarkable cells are easily abundantly available couple with less invasive procedure in isolating comparing to bone marrow aspiration. Here we proposed dental stem cells as candidate for cardiac regeneration based on its immature characteristic and propensity towards cardiac lineage via PI3-Kinase/Aktsignalling pathway.
    Matched MeSH terms: Cardiovascular Diseases/therapy*
  10. Adam M, Oh SL, Sudarshan VK, Koh JE, Hagiwara Y, Tan JH, et al.
    Comput Methods Programs Biomed, 2018 Jul;161:133-143.
    PMID: 29852956 DOI: 10.1016/j.cmpb.2018.04.018
    Cardiovascular diseases (CVDs) are the leading cause of deaths worldwide. The rising mortality rate can be reduced by early detection and treatment interventions. Clinically, electrocardiogram (ECG) signal provides useful information about the cardiac abnormalities and hence employed as a diagnostic modality for the detection of various CVDs. However, subtle changes in these time series indicate a particular disease. Therefore, it may be monotonous, time-consuming and stressful to inspect these ECG beats manually. In order to overcome this limitation of manual ECG signal analysis, this paper uses a novel discrete wavelet transform (DWT) method combined with nonlinear features for automated characterization of CVDs. ECG signals of normal, and dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM) and myocardial infarction (MI) are subjected to five levels of DWT. Relative wavelet of four nonlinear features such as fuzzy entropy, sample entropy, fractal dimension and signal energy are extracted from the DWT coefficients. These features are fed to sequential forward selection (SFS) technique and then ranked using ReliefF method. Our proposed methodology achieved maximum classification accuracy (acc) of 99.27%, sensitivity (sen) of 99.74%, and specificity (spec) of 98.08% with K-nearest neighbor (kNN) classifier using 15 features ranked by the ReliefF method. Our proposed methodology can be used by clinical staff to make faster and accurate diagnosis of CVDs. Thus, the chances of survival can be significantly increased by early detection and treatment of CVDs.
    Matched MeSH terms: Cardiovascular Diseases/diagnosis*
  11. Ponniah JP, Shamsul AS, Adam BM
    Med J Malaysia, 2012 Dec;67(6):601-5.
    PMID: 23770953 MyJurnal
    The aim of this study is to determine risks factor of mortality among patient with post percutaneous coronary intervention. Estimation of post operative mortality risk factor is essential for planning prevention modalities. This is retrospective cohort study based on secondary data extracted from the National Cardiovascular Disease Database (NCVD-ACS and NCVD PCI). Both these registries were interlinked and was further matched to JPN (Jabatan Pendaftaran Negara/National registration Department) to assess mortality among the patients who underwent PCI and all death which occurred in between 2007, 2008 and 2009. There were 630 patients in this studied. Age, history of diabetes mellitus, peripheral vascular, renal failure and previous percutaneous coronary intervention were univariately associated with mortality. However based on logistics stepwise method, only age and history of renal failure had showed statistically significant and sizeable odds ratio in predicting the patient died of coronary death. Older age and renal failure are the predicting factors for mortality among patients with post percutaneous coronary intervention.
    Matched MeSH terms: Cardiovascular Diseases
  12. Naqvi AA, Hassali MA, Aftab MT
    J Pak Med Assoc, 2019 Mar;69(3):389-398.
    PMID: 30890833
    OBJECTIVE: The study aimed to evaluate literature on rheumatoid arthritis disease in Pakistani patients, to have an understanding about its epidemiology, clinical aspects and socio-economic determinants.

    METHODS: The review study was conducted from December 2017, to May 2018. An online search was conducted in international and local health databases using appropriate search keywords as well as scanning reference lists of related articles. Literature published after year 2000 that reported epidemiological, demographic, clinical and socioeconomic data of Pakistani rheumatoid arthritis patients was included. Meta-analysis was performed where possible. This systematic review was registered on the international prospective register of systematic reviews PROSPERO (CRD42018090582).

    RESULTS: Of the 334 research articles found, 29 (8.7%) were selected. Patients were mostly females, but no study explored impact of disease on household and family role functioning of rheumatoid arthritis-affected women in Pakistan. Most patients were uneducated (55%) and unemployed; had low disease knowledge (N = 149, 74.5%) and poor adherence to disease-modifying anti-rheumatic drugs (N = 23, 23%). Point prevalence of rheumatoid arthritis reported from Karachi was high at 26.9%. Moderate disease activity, i.e., 4.5}0.7 and mild functional disability (N = 66, 51.6%) were seen in RA patients. Almost half (N = 799, 46.9%) had comorbidities. Almost a fifth proportion of RA patients had dyslipidaemia as a comorbidity (N = 134, 16.77%) and higher cardiovascular risk score as modifiable risk factor. Undiagnosed depression (N = 134, 58.3%) and low bone mineral density (N = 93, 40.6%) were reported in RA patients. Direct monthly treatment cost of disease was significantly high considering patients' socio-economic status, i.e., USD 16.47 - 100.68. Most commonly used drug was methotrexate.

    CONCLUSIONS: There is a paucity of data on Pakistani rheumatoid arthritis patients' demographic and socio-economic parameters, especially the gender element.

    Matched MeSH terms: Cardiovascular Diseases/epidemiology
  13. Khani Jeihooni A, Jormand H, Saadat N, Hatami M, Abdul Manaf R, Afzali Harsini P
    BMC Cardiovasc Disord, 2021 Dec 07;21(1):589.
    PMID: 34876014 DOI: 10.1186/s12872-021-02399-3
    BACKGROUND: Nutritional factors have been identified as preventable risk factors for cardiovascular disease; this study aimed to investigate the application of the Theory of Planned Behavior (TPB) in nutritional behaviors related to cardiovascular diseases among the women in Fasa city, Fars province, Iran.

    METHODS: The study was conducted in two stages. First, the factors affecting nutritional behaviors associated with cardiovascular disease on 350 women who were referred to Fasa urban health centers were determined based on the TPB. In the second stage, based on the results of a cross-sectional study, quasi-expeimental study was performed on 200 women covered by Fasa health centers. The questionnaire used for the study was a questionnaire based on TPB. The questionnaire was completed by the experimental and control groups before and three months after the intervention. Data were analyzed by SPSS software using logistic regression, paired t-test, independent sample t-test, and chi-square test. The level of significance is considered 0.05.

    RESULT: The constructs of attitude, subjective norms, and perceived behavioral control (PBC) were predictors of nutritional behaviors associated with cardiovascular disease in women. The constructs predicted 41.6% of the behavior. The results showed that mean scores of attitude, subjective norms, PBC, intention, nutritional performance related to the cardiovascular disease before intervention were, respectively, 24.32, 14.20, 18.10, 13.37 and 16.28, and after the intervention, were, respectively, 42.32, 25.40, 33.72, 30.13 and 41.38. All the constructs except the attitude in the intervention group were significantly higher (p cardiovascular disease in women. Considering the role of mothers in providing family food baskets and the effect of their nutritional behaviors on family members, the education of this group can promote healthy eating behaviors in the community and family.

    Matched MeSH terms: Cardiovascular Diseases/diagnosis; Cardiovascular Diseases/etiology; Cardiovascular Diseases/prevention & control*
  14. Othman J, Sahani M, Mahmud M, Ahmad MK
    Environ Pollut, 2014 Jun;189:194-201.
    PMID: 24682070 DOI: 10.1016/j.envpol.2014.03.010
    This study assessed the economic value of health impacts of transboundary smoke haze pollution in Kuala Lumpur and adjacent areas in the state of Selangor, Malaysia. Daily inpatient data from 2005, 2006, 2008, and 2009 for 14 haze-related illnesses were collected from four hospitals. On average, there were 19 hazy days each year during which the air pollution levels were within the Lower Moderate to Hazardous categories. No seasonal variation in inpatient cases was observed. A smoke haze occurrence was associated with an increase in inpatient cases by 2.4 per 10,000 populations each year, representing an increase of 31 percent from normal days. The average annual economic loss due to the inpatient health impact of haze was valued at MYR273,000 ($91,000 USD).
    Matched MeSH terms: Cardiovascular Diseases/epidemiology
  15. Sazlina SG, Sooryanarayana R, Ho BK, Omar MA, Krishnapillai AD, Mohd Tohit N, et al.
    PLoS One, 2020;15(10):e0240826.
    PMID: 33085718 DOI: 10.1371/journal.pone.0240826
    Study on cardiovascular disease (CVD) risk factors and their prevalence among the older people in Malaysia is limited. We aimed to determine the prevalence and factors associated with CVD risk factors using the non-laboratory Framingham Generalized 10-Year CVD risk score among older people in Malaysia. This was a population-based cross-sectional study using data of 3,375 participants aged ≥60 years from the National Health and Morbidity Survey 2015. Sociodemographic, health factors and clinical assessments (anthropometry and blood pressure) were included. Complex survey analysis was used to obtain prevalence with 95% confidence intervals (CI). We applied ordinal regression to determine the factors associated with CVD risk. The prevalence for the high 10-year CVD risk was 72.1%. Body mass index was higher among those aged 60-69 years in men (25.4kg/m2, 95%CI 25.1-25.8) and women (26.7kg/m2, 95%CI 26.3-27.1) than the other age groups. The factors associated with moderate and high 10-year CVD risk were Malay ethnicity (Odds Ratio(OR) 0.76, 95%CI 0.63-0.92, p = 0.004), unmarried status (OR 1.55, 95%CI 1.22-1.97, p<0.001) and physically inactive (OR 0.72, 95%CI 0.55-0.95, p = 0.020). There is a need for future study to evaluate preventive strategies to improve the health of older people in order to promote healthy ageing.
    Matched MeSH terms: Cardiovascular Diseases/epidemiology*; Cardiovascular Diseases/physiopathology*
  16. Nurliyana Juhan, Yong Zulina Zubairi, Zarina Mohd Khalid, Ahmad Syadi Mahmood Zuhdi
    MATEMATIKA, 2018;34(101):15-23.
    MyJurnal
    Cardiovascular disease (CVD) includes coronary heart disease, cerebrovascular disease (stroke), peripheral artery disease, and atherosclerosis of the aorta. All females face the threat of CVD. But becoming aware of symptoms and signs is a great challenge since most adults at increased risk of cardiovascular disease (CVD) have no symptoms or obvious signs especially in females. The symptoms may be identified by the assessment of their risk factors. The Bayesian approach is a specific way in dealing with this kind of problem by formalizing a priori beliefs and of combining them with the available observations. This study aimed to identify associated risk factors in CVD among female patients presenting with ST Elevation Myocardial Infarction (STEMI) using Bayesian logistic regression and obtain a feasible model to describe the data. A total of 874 STEMI female patients in the National Cardiovascular Disease Database-Acute Coronary Syndrome (NCVD-ACS) registry year 2006-2013 were analysed. Bayesian Markov Chain Monte Carlo (MCMC) simulation approach was applied in the univariate and multivariate analysis. Model performance was assessed through the model calibration and discrimination. The final multivariate model of STEMI female patients consisted of six significant variables namely smoking, dyslipidaemia, myocardial infarction (MI), renal disease, Killip class and age group. Females aged 65 years and above have higher incidence of CVD and mortality is high among female patients with Killip class IV. Also, renal disease was a strong predictor of CVD mortality. Besides, performance measures for the model was considered good. Bayesian logistic regression model provided a better understanding on the associated risk factors of CVD for female patients which may help tailor prevention or treatment plans more effectively.
    Matched MeSH terms: Cardiovascular Diseases*
  17. Huri HZ, Ling DY, Ahmad WA
    Drug Des Devel Ther, 2015;9:4735-49.
    PMID: 26316711 DOI: 10.2147/DDDT.S87294
    PURPOSE: Cardiovascular disease (CVD) is a macrovascular complication in patients with type 2 diabetes mellitus (T2DM). To date, glycemic control profiles of antidiabetic drugs in cardiovascular (CV) complications have not been clearly elucidated. Therefore, this study was conducted retrospectively to assess the association of antidiabetic drugs and glycemic control with CV profiles in T2DM patients. The association of concurrent medications and comorbidities with glycemic control was also investigated.

    METHODS: A total of 220 T2DM patients from the University of Malaya Medical Centre, Malaysia, who had at least one CV complication and who had been taking at least one antidiabetic drug for at least 3 months, were included. The associations of antidiabetics, cardiovascular diseases, laboratory parameters, concurrent medications, comorbidities, demographics, and clinical characteristics with glycemic control were investigated.

    RESULTS: Sulfonylureas in combination (P=0.002) and sulfonylurea monotherapy (P<0.001) were found to be associated with good glycemic control, whereas insulin in combination (P=0.051), and combination biguanides and insulin therapy (P=0.012) were found to be associated with poor glycemic control. Stroke (P=0.044) was the only type of CVD that seemed to be significantly associated with good glycemic control. Other factors such as benign prostatic hyperplasia (P=0.026), elderly patients (P=0.018), low-density lipoprotein cholesterol levels (P=0.021), and fasting plasma glucose (P<0.001) were found to be significantly correlated with good glycemic control.

    CONCLUSION: Individualized treatment in T2DM patients with CVDs can be supported through a better understanding of the association between glycemic control and CV profiles in T2DM patients.

    Matched MeSH terms: Cardiovascular Diseases/blood; Cardiovascular Diseases/diagnosis; Cardiovascular Diseases/epidemiology*; Cardiovascular Diseases/therapy
  18. Moradipoor S, Ismail P, Etemad A, Wan Sulaiman WA, Ahmadloo S
    Biomed Res Int, 2016;2016:1845638.
    PMID: 27781209 DOI: 10.1155/2016/1845638
    Endothelial dysfunction appears to be an early sign indicating vascular damage and predicts the progression of atherosclerosis and cardiovascular disorders. Extensive clinical and experimental evidence suggests that endothelial dysfunction occurs in Type 2 Diabetes Mellitus (T2DM) and prediabetes patients. This study was carried out with an aim to appraise the expression levels in the peripheral blood of 84 genes related to endothelial cells biology in patients with diagnosed T2DM or prediabetes, trying to identify new genes whose expression might be changed under these pathological conditions. The study covered a total of 45 participants. The participants were divided into three groups: group 1, patients with T2DM; group 2, patients with prediabetes; group 3, control group. The gene expression analysis was performed using the Endothelial Cell Biology RT(2) Profiler PCR Array. In the case of T2DM, 59 genes were found to be upregulated, and four genes were observed to be downregulated. In prediabetes patients, increased expression was observed for 49 genes, with two downregulated genes observed. Our results indicate that diabetic and prediabetic conditions change the expression levels of genes related to endothelial cells biology and, consequently, may increase the risk for occurrence of endothelial dysfunction.
    Matched MeSH terms: Cardiovascular Diseases/genetics; Cardiovascular Diseases/metabolism
  19. Teng S, Khong KW, Pahlevan Sharif S, Ahmed A
    JMIR Public Health Surveill, 2020 10 01;6(4):e19618.
    PMID: 33001036 DOI: 10.2196/19618
    BACKGROUND: Poor nutrition and food selection lead to health issues such as obesity, cardiovascular disease, diabetes, and cancer. This study of YouTube comments aims to uncover patterns of food choices and the factors driving them, in addition to exploring the sentiments of healthy eating in networked communities.

    OBJECTIVE: The objectives of the study are to explore the determinants, motives, and barriers to healthy eating behaviors in online communities and provide insight into YouTube video commenters' perceptions and sentiments of healthy eating through text mining techniques.

    METHODS: This paper applied text mining techniques to identify and categorize meaningful healthy eating determinants. These determinants were then incorporated into hypothetically defined constructs that reflect their thematic and sentimental nature in order to test our proposed model using a variance-based structural equation modeling procedure.

    RESULTS: With a dataset of 4654 comments extracted from YouTube videos in the context of Malaysia, we apply a text mining method to analyze the perceptions and behavior of healthy eating. There were 10 clusters identified with regard to food ingredients, food price, food choice, food portion, well-being, cooking, and culture in the concept of healthy eating. The structural equation modeling results show that clusters are positively associated with healthy eating with all P values less than .001, indicating a statistical significance of the study results. People hold complex and multifaceted beliefs about healthy eating in the context of YouTube videos. Fruits and vegetables are the epitome of healthy foods. Despite having a favorable perception of healthy eating, people may not purchase commonly recognized healthy food if it has a premium price. People associate healthy eating with weight concerns. Food taste, variety, and availability are identified as reasons why Malaysians cannot act on eating healthily.

    CONCLUSIONS: This study offers significant value to the existing literature of health-related studies by investigating the rich and diverse social media data gleaned from YouTube. This research integrated text mining analytics with predictive modeling techniques to identify thematic constructs and analyze the sentiments of healthy eating.

    Matched MeSH terms: Cardiovascular Diseases
  20. Elhaj FA, Salim N, Harris AR, Swee TT, Ahmed T
    Comput Methods Programs Biomed, 2016 Apr;127:52-63.
    PMID: 27000289 DOI: 10.1016/j.cmpb.2015.12.024
    Arrhythmia is a cardiac condition caused by abnormal electrical activity of the heart, and an electrocardiogram (ECG) is the non-invasive method used to detect arrhythmias or heart abnormalities. Due to the presence of noise, the non-stationary nature of the ECG signal (i.e. the changing morphology of the ECG signal with respect to time) and the irregularity of the heartbeat, physicians face difficulties in the diagnosis of arrhythmias. The computer-aided analysis of ECG results assists physicians to detect cardiovascular diseases. The development of many existing arrhythmia systems has depended on the findings from linear experiments on ECG data which achieve high performance on noise-free data. However, nonlinear experiments characterize the ECG signal more effectively sense, extract hidden information in the ECG signal, and achieve good performance under noisy conditions. This paper investigates the representation ability of linear and nonlinear features and proposes a combination of such features in order to improve the classification of ECG data. In this study, five types of beat classes of arrhythmia as recommended by the Association for Advancement of Medical Instrumentation are analyzed: non-ectopic beats (N), supra-ventricular ectopic beats (S), ventricular ectopic beats (V), fusion beats (F) and unclassifiable and paced beats (U). The characterization ability of nonlinear features such as high order statistics and cumulants and nonlinear feature reduction methods such as independent component analysis are combined with linear features, namely, the principal component analysis of discrete wavelet transform coefficients. The features are tested for their ability to differentiate different classes of data using different classifiers, namely, the support vector machine and neural network methods with tenfold cross-validation. Our proposed method is able to classify the N, S, V, F and U arrhythmia classes with high accuracy (98.91%) using a combined support vector machine and radial basis function method.
    Matched MeSH terms: Cardiovascular Diseases
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