Showing 321 - 340 results of 416 for search '"Cleveland"', query time: 0.05s Refine Results
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    The Association Between Medication Adherence, Internalized Stigma and Social Support Among Outpatients with Major Depressive Disorder in a Malaysian Hospital: A Cross-Sectional Stu... by Halim R, Kaur M, Syed Mokhtar SS, Chemi N, Sajatovic M, Tan YK, Siau CS, Ng CG

    Published 2025-02-01
    “…Rahilah Halim,1,* Manveen Kaur,2,* Sharifah Suziah Syed Mokhtar,1 Norliza Chemi,1 Martha Sajatovic,3 Yee Kee Tan,4 Ching Sin Siau,4 Chong Guan Ng2 1Department of Psychiatry and Mental Health, Hospital Kajang, Kajang, Selangor, Malaysia; 2Psychological Medicine Department, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia; 3Neurological and Behavioral Outcomes Center, University Hospital Cleveland Medical Center & Case Western Reserve University School of Medicine, Cleveland, OH, USA; 4Centre for Community Health Studies (Reach), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia*These authors contributed equally to this workCorrespondence: Manveen Kaur, Psychological Medicine Department, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia, Email manveen@um.edu.my Ching Sin Siau, Centre for Community Health Studies, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Wilayah Persekutuan, Malaysia, Email chingsin.siau@ukm.edu.myBackground: Internalized stigma and medication non-adherence pose significant challenges for treating major depressive disorder (MDD), leading to disability, increased suicide risk, and morbidity. …”
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    Adaptive Mixed-Attribute Data Clustering Method Based on Density Peaks by Shihua Liu

    Published 2022-01-01
    “…Experimental results on real University of California-Irvine (UCI) datasets showed that the proposed AMDPC algorithm could realize adaptive clustering of mixed-attribute data, can automatically obtain the correct number of clusters, and improved the clustering accuracy of all datasets by more than 22.58%, by 24.25%, by 28.03%, by 22.5%, and by 10.12% for the Heart, Cleveland, Credit, Acute, and Adult datasets compared to that of the traditional K-prototype algorithm, respectively. …”
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    Comparative Study on Heart Disease Prediction Using Feature Selection Techniques on Classification Algorithms by Kaushalya Dissanayake, Md Gapar Md Johar

    Published 2021-01-01
    “…., decision tree, random forest, support vector machine, K-nearest neighbor, logistic regression, and Gaussian naive Bayes, have been applied to Cleveland heart disease dataset. The feature subset selected by the backward feature selection technique has achieved the highest classification accuracy of 88.52%, precision of 91.30%, sensitivity of 80.76%, and f-measure of 85.71% with the decision tree classifier.…”
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    Diagnosis of Coronary Heart Disease by Using Hybrid Intelligent Systems Based on the Whale Optimization Algorithm, Simulated Annealing and Support Vector Machine by Zeinab Hassani, Mahin Khosravi

    Published 2020-09-01
    “…The proposed approach is evaluated using the Cleveland Heart Disease Data Collection in the UCI database. …”
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