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Zoran Bukumiric

Researcher at University of Belgrade

Publications -  146
Citations -  1194

Zoran Bukumiric is an academic researcher from University of Belgrade. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 12, co-authored 91 publications receiving 759 citations. Previous affiliations of Zoran Bukumiric include Universiteti i Prishtinës.

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Reliability of the Hamilton Rating Scale for Depression: A meta-analysis over a period of 49 years

TL;DR: Figures indicate good overall levels of internal consistency, inter-rater and test-retest reliability, but some HRSD items do not appear to possess a satisfactory reliability.
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Reveal, Don't Conceal: Transforming Data Visualization to Improve Transparency.

TL;DR: A systematic review of studies published in top peripheral vascular disease journals to determine what types of figures are used, and to assess the prevalence of suboptimal data visualization practices, found that 47.7% of papers used bar graphs to present continuous data.
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Depression and quality of sleep in maintenance hemodialysis patients.

TL;DR: Depression and poor sleep quality are frequent and interrelated among HD patients and a statistically significant positive correlation was found between BDI and PSQI.
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The prognostic significance of the circulating neuroendocrine markers chromogranin A, pro-gastrin-releasing peptide, and neuron-specific enolase in patients with small-cell lung cancer

TL;DR: There is a potential role for ProGRP, NSE, and CGA in both staging and prognosing survival in SCLC patients, and a statistically significant association between survival and PS, disease stage, andCGA, pro-gastrin-releasing peptide, and neuron-specific enolase levels is found.
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Improving Education in Medical Statistics: Implementing a Blended Learning Model in the Existing Curriculum.

TL;DR: Examination scores for the blended learning student group were higher than for the on-site student group for both final statistics score and knowledge test scores, and implementation of blended learning approaches can be considered an attractive, cost-effective, and efficient alternative to traditional classroom training in medical statistics.