Browsing by Author "Prameyuda Suwannasing"

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    K4ThaiHealth: A prototype for Thai routine medical research knowledge extraction sharing
    (2018-11-05) Jarernsri Mitrpanont; Wudhichart Sawangphol; Thanita Vithantirawat; Sinattaya Paengkaew; Prameyuda Suwannasing; Mahidol University
    © 2018 IEEE. 'Routine to Research' (R2R) is well known for Thai research related to the development of routine works of medical and public health practitioners. R2R research contains useful practical knowledge beneficial to the health of Thai people. However, this knowledge cannot be shared easily because it is unstructured and not classified text, moreover, no tool for R2R Thai knowledge sharing yet. In this research, we attempt to use text mining techniques to get insights of R2R research data and the K4ThaiHealth is first implemented as a prototype for basic R2R knowledge sharing. A set of basic medical corpus are developed using Thai medical International Statistical Classification of Diseases and Related Health Problems (ICD10TM) and several resources. They are used for R2R Thai medical text classification and key terms relationship extraction. The results are classified into diseases, organs, symptoms, and others. K4ThaiHealth is then used as a knowledge sharing prototype to offer health and medical practice knowledge extracted from R2R data sharing to Thai people. R2R WordCloud and R2R WordNet are used to display the diseases knowledge extracted from R2R research data and their relationships to diseases, organs, symptoms and others are visualized.
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    A study on using Python vs Weka on dialysis data analysis
    (2018-01-12) Jarernsri Mitrpanont; Wudhichart Sawangphol; Thanita Vithantirawat; Sinattaya Paengkaew; Prameyuda Suwannasing; Atthapan Daramas; Yi Cheng Chen; National Central University Taiwan; Mahidol University
    © 2017 IEEE. Health data has been drastically increasing in capacity and variety. Due to large and complex collection of datasets, it is difficult to process data using traditional data processing techniques. Machine Learning techniques, such as KNN and Naïve Bayes, have been used. Python and Weka are tools that are widely used in the field of data analytics. Therefore, this paper gives the comprehensive comparison between both tools together with some machine learning algorithms on data analytic of Dialysis Dataset. The results show that using Python provides the better performance in term of correct/incorrect instances, precision, and recall.