BackgroundThe aim of this study is to develop a simple and reliable hybrid decision support model by combining statistical analysis and decision tree algorithms to ensure high accuracy of early diagnosis in patients with suspected acute appendicitis and to identify useful decision rules.MethodsWe enrolled 326 patients who attended an emergency medical center complaining mainly of acute abdominal pain. Statistical analysis approaches were used as a feature selection process in the design of decision support models, including the Chi-square test, Fisher's exact test, the Mann-Whitney U-test (p < 0.01), and Wald forward logistic regression (entry and removal criteria of 0.01 and 0.05, or 0.05 and 0.10, respectively). The final decision support models were constructed using the C5.0 decision tree algorithm of Clementine 12.0 after pre-processing.ResultsOf 55 variables, two subsets were found to be indispensable for early diagnostic knowledge discovery in acute appendicitis. The two subsets were as follows: (1) lymphocytes, urine glucose, total bilirubin, total amylase, chloride, red blood cell, neutrophils, eosinophils, white blood cell, complaints, basophils, glucose, monocytes, activated partial thromboplastin time, urine ketone, and direct bilirubin in the univariate analysis-based model; and (2) neutrophils, complaints, total bilirubin, urine glucose, and lipase in the multivariate analysis-based model. The experimental results showed that the model with univariate analysis (80.2%, 82.4%, 78.3%, 76.8%, 83.5%, and 80.3%) outperformed models using multivariate analysis (71.6%, 69.3%, 73.7%, 69.7%, 73.3%, and 71.5% with entry and removal criteria of 0.01 and 0.05; 73.5%, 66.0%, 80.0%, 74.3%, 72.9%, and 73.0% with entry and removal criteria of 0.05 and 0.10) in terms of accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under ROC curve, during a 10-fold cross validation. A statistically significant difference was detected in the pairwise comparison of ROC curves (p < 0.01, 95% CI, 3.13-14.5; p < 0.05, 95% CI, 1.54-13.1). The larger induced decision model was more effective for identifying acute appendicitis in patients with acute abdominal pain, whereas the smaller induced decision tree was less accurate with the test data.ConclusionsThe decision model developed in this study can be applied as an aid in the initial decision making of clinicians to increase vigilance in cases of suspected acute appendicitis.

Abstract. [Purpose] This study examined the relationship between the subjective quality of life of clinical physical therapists and the factors affecting their work satisfaction. [Subjects and Methods] A questionnaire was given to 101 clinical physical therapists who worked in medical institutions in A region from October to November 2009. [Results] Personal environment factors, such as marital status, education, work experience, etc, were found to affect the subjective quality of life. Hierarchical regression revealed job stress, self-esteem, job satisfaction and support of superiors or co-workers to be associated with the subjective quality of life of clinical physical therapists.[Conclusion] Several factors were found to affect the level of work satisfaction, which affected the subjective quality of life. These results can be used as base data for the development of programs for improving the subjective quality of life of clinical physical therapists.

Abstract.[Purpose] The purpose of this study was to investigate clinical aspects of screen test tools for central neuropathic pain in thalamic stroke patients. [Subjects and Methods] Seven thalamic stroke patients were recruited as subjects. To classify the subjects into central neuropathic pain and non-neuropathic pain groups, the Leeds assessment of neuropathic symptoms and signs (LANSS) was used. Four patients were classified as having central neuropathic pain. To evaluate the central neuropathic pain, the quantitative somatosensory test, the median nerve somatosensory evoked potentials (SEPs), magnetic resonance imaging (MRI), and functional MRI (fMRI) were performed on average 31.5 months after stroke.[Results] The quantitative somatosensory test did not show a correlation between the central neuropathic pain group and the non-neuropathic pain group. The SEPs on the affected side showed a response in one of the patients without central neuropathic pain, and responses on the unaffected side were normal for all of the patients. MRI-based thalamic localization data indicate that this method is limited in its ability to distinguish the central neuropathic pain in thalamic stroke patients. Results of fMRI show that the secondary somatosensory areas of the central neuropathic pain group were more activated than those of nonneuropathic pain group. [Conclusion] Based on the results, we verified that functional MRI is useful for evaluating the central neuropathic pain in thalamic stroke patients.

ObjectivesCongenital muscular torticollis, a common disorder that refers to the shortening of the sternocleidomastoid in infants, is sensitive to correction through physical therapy when treated early. If physical therapy is unsuccessful, surgery is required. In this study, we developed a support vector regression model for congenital muscular torticollis to investigate the prognosis of the physical therapy treatent in infants.MethodsFifty-nine infants with congenital muscular torticollis received physical therapy until the degree of neck tilt was less than 5°. After treatment, the mass diameter was reevaluated. Based on the data, a support vector regression model was applied to predict the prognoses.Results10-, 20-, and 50-fold cross-tabulation analyses for the proposed model were conducted based on support vector regression and conventional multi-regression method based on least squares. The proposed methodbased on support vector regression was robust and enabled the effective analysis of even a small amount of data containing outliers.ConclusionsThe developed support vector regression model is an effective prognostic tool for infants with congenital muscular torticollis who receive physical therapy.

SUMMARY The thresholding results for gray level images depend greatly on the thresholding method applied. However, this letter proposes a histogram equalization-based thresholding algorithm that makes the thresholding results insensitive to the thresholding method applied. Experimental results are presented to demonstrate the effectiveness of the proposed thresholding algorithm.