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International Journal of Medical, Medicine and Health Sciences

ISSN: 2517-9969

Total 23 content found

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The Practical Delivery Room Experience of Nursing Students at Suranaree University of Technology

Year: 2012 Volume: 6 Issue: 11 519 - 522 Pages

Abstract: The purpose of this study was to study the practical delivery room experience of nursing students. The respondents were 6 junior nursing students of Suranaree University of Technology who had a direct experience from practicing in a delivery room between January 9 and March 30, 2012 as part of Nursing Care of the Family and Midwifery 3. The data was collected by using in-depth interview, observation, and reflective report. The results of the study found that the practical delivery room experience of nursing students consisted of three issues: 1) stress and coping with stress during practical exercise, 2) changes in daily routine, and 3) source during practical exercise. The results of this study would lead to the understanding of the meaning of the practical exercise of nursing students.

A Fuzzy Tumor Volume Estimation Approach Based On Fuzzy Segmentation of MR Images

Year: 2012 Volume: 6 Issue: 11 513 - 518 Pages

Abstract: Quantitative measurements of tumor in general and tumor volume in particular, become more realistic with the use of Magnetic Resonance imaging, especially when the tumor morphological changes become irregular and difficult to assess by clinical examination. However, tumor volume estimation strongly depends on the image segmentation, which is fuzzy by nature. In this paper a fuzzy approach is presented for tumor volume segmentation based on the fuzzy connectedness algorithm. The fuzzy affinity matrix resulting from segmentation is then used to estimate a fuzzy volume based on a certainty parameter, an Alpha Cut, defined by the user. The proposed method was shown to highly affect treatment decisions. A statistical analysis was performed in this study to validate the results based on a manual method for volume estimation and the importance of using the Alpha Cut is further explained.

Gene Expression Signature for Classification of Metastasis Positive and Negative Oral Cancer in Homosapiens

Year: 2012 Volume: 6 Issue: 11 506 - 512 Pages

Abstract: Cancer classification to their corresponding cohorts has been key area of research in bioinformatics aiming better prognosis of the disease. High dimensionality of gene data has been makes it a complex task and requires significance data identification technique in order to reducing the dimensionality and identification of significant information. In this paper, we have proposed a novel approach for classification of oral cancer into metastasis positive and negative patients. We have used significance analysis of microarrays (SAM) for identifying significant genes which constitutes gene signature. 3 different gene signatures were identified using SAM from 3 different combination of training datasets and their classification accuracy was calculated on corresponding testing datasets using k-Nearest Neighbour (kNN), Fuzzy C-Means Clustering (FCM), Support Vector Machine (SVM) and Backpropagation Neural Network (BPNN). A final gene signature of only 9 genes was obtained from above 3 individual gene signatures. 9 gene signature-s classification capability was compared using same classifiers on same testing datasets. Results obtained from experimentation shows that 9 gene signature classified all samples in testing dataset accurately while individual genes could not classify all accurately.