• Radiation Oncology Journal
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• v.28 no.4
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• pp.193-204
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• 2010

Purpose: To analyze the treatment outcomes, complications, prognostic factors after a long-term follow-up of patients with nasopharyngeal carcinoma treated with radiation therapy (RT) alone or concurrent chemoradiation therapy (CCRT). Materials and Methods: Between December 1981 and December 2006, 190 eligible patients with non-metastatic nasopharyngeal carcinoma were treated at our department with a curative intent. Of these patients, 103 were treated with RT alone and 87 patients received CCRT. The median age was 49 years (range, 8~78 years). The distributions of clinical stage according to the AJCC 6th edition included I: 7 (3.6%), IIA: 8 (4.2%), IIB: 33 (17.4%), III: 82 (43.2%), IVA: 31 (16.3%), IVB: 29 (15.3%). The accumulated radiation doses to the primary tumor ranged from 66.6~87.0 Gy (median, 72 Gy). Treatment outcomes and prognostic factors were retrospectively analyzed. Acute and late toxicities were assessed using the RTOG criteria. Results: A total of 96.8% (184/190) of patients completed the planned treatment. With a mean follow-up of 73 months (range, 2~278 months; median, 52 months), 93 (48.9%) patients had relapses that were local 44 (23.2%), nodal 13 (6.8%), or distant 49 (25.8%). The 5- and 10-year overall survival (OS), disease-free survival (DFS), and disease-specific survival (DSS) rates were 55.6% and 44.5%, 54.8% and 51.3%, in addition to 65.3% and 57.4%, respectively. Multivariate analyses revealed that CCRT, age, gender, and stage were significant prognostic factors for OS. The CCRT and gender were independent prognostic factors for both DFS and DSS. There was no grade 4 or 5 acute toxicity, but grade 3 mucositis and hematologic toxicity were present in 42 patients (22.1%) and 18 patients (9.5%), respectively. During follow-up, grade 3 hearing loss in 9 patients and trismus in 6 patients were reported. Conclusion: The results of our study were in accordance with findings of previous studies and we confirmed that CCRT, low stage, female gender, and young age were related to improvement in OS. However, there are limitations in the locoregional control that can be achieved by CCRT with 20 conventional radiation therapy. This observation has led to further studies on clarifying the efficacy of concurrent chemotherapy by intensity modulated radiation therapy.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.1
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• pp.127-135
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• 2014

Purpose : By taking advantage of each imaging modality, the use of fused CT/MRI image has increased in prostate cancer radiation therapy. However, fusion uncertainty may cause partial target miss or normal organ overdose. In order to complement such limitation, our hospital acquired MRI image (Planning MRI) by setting up patients with the same fixing tool and posture as CT simulation. This study aims to evaluate the usefulness of the Planning MRI through comparing and analyzing the diagnostic MRI image and Planning MRI image. Materials and Methods : This study targeted 10 patients who had been diagnosed with prostate cancer and prescribed nonhormone and definitive RT 70 Gy/28 fx from August 2011 to July 2013. Each patient had both CT and MRI simulations. The MRI images were acquired within one half hour after the CT simulation. The acquired CT/MRI images were fused primarily based on bony structure matching. This study measured the volume of prostate in the images of Planning MRI and diagnostic MRI. The diameters at the craniocaudal, anteroposterior and left-to-right directions from the center of prostate were measured in order to compare changes in the shape of prostate. Results : As a result of comparing the volume of prostate in the images of Planning MRI and diagnostic MRI, they were found to be $25.01cm^3$(range $15.84-34.75cm^3$) and $25.05cm^3$(range $15.28-35.88cm^3$) on average respectively. The diagnostic MRI had an increase of 0.12 % as compared with the Planning MRI. On the planning MRI, there was an increase in the volume by $7.46cm^3$(29 %) at the transition zone directions, and there was a decrease in the volume by $8.52cm^3$(34 %) in the peripheral zone direction. As a result of measuring the diameters at the craniocaudal, anteroposterior and left-to-right directions in the prostate, the Planning MRI was found to have on average 3.82cm, 2.38cm and 4.59cm respectively and the diagnostic MRI was found to have on average 3.37cm, 2.76cm and 4.51cm respectively. All three prostate diameters changed and the change was significant in the Planning MRI. On average, the anteroposterior prostate diameter decrease by 0.38cm(13 %). The mean right-to-left and craniocaudal diameter increased by 0.08cm(1.6 %) and 0.45cm(13 %), respectively. Conclusion : Based on the results of this study, it was found that the total volumes of prostate in the Planning MRI and the diagnostic MRI were not significantly different. However, there was a change in the shape and partial volume of prostate due to the insertion of prostate balloon tube to the rectum. Thus, if the Planning MRI images were used when conducting the fusion of CT/MRI images, it would be possible to include the target in the CTV without a loss as much as the increased volume in the transition zone. Also, it would be possible to reduce the radiation dose delivered to the rectum through separating more clearly the reduction of peripheral zone volume. Therefore, the author of this study believes that acquisition of Planning MRI image should be made to ensure target delineation and localization accuracy.

• Journal of Oral Medicine and Pain
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• v.31 no.4
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• pp.297-316
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• 2006

The increasing tendency of medical disputes is one of the remarkable social phenomena. Especially we must not overlook the phenomenon that production and circulation of information related to medical accidents is increasing rapidly through the internet. In this research, we evaluated the web sites which provide the information related to medical accidents using the keyword "medical accidents" in March 2006, and classified the 28 web sites according to the kinds of establishers. We also analyzed the contents of the sites, and checked and compared the current status of the web sites and problems that have to be improved. Finally, we suggested the possible solutions to prevent medical accidents. The detailed results were listed below. 1. Medical practitioners, general public, and lawyers were all familiar with and prefer the term "medical accidents" mainly. 2. In the number of sites searched by the keyword "medical accidents", lawyer had the most sites and medical practitioners had the least ones. 3. Many sites by general public and lawyers had their own medical record analysts but there was little professional analysts for dentistry. 4. General public were more interested in the prevention of medical accidents but the lawyers were more interested in the process after medical accidents. The sites by medical practitioners dealt with the least remedies of medical accidents, compared with other sites. 5. General public wanted the third party such as government intervention into the disputes including the medical dispute arbitration law or/and the establishment of independent medical dispute judgment institution. 6. In the comparison among the establishers of web sites, medical practitioners dealt with the least examples of medical accidents. 7. The suggestion of cases in counseling articles related to dental accidents were considered less importantly than the reality. 8. Whereas there were many articles about domestic cases related to the bloody dental treatment, in the open counseling articles the number of dental treatment regarding to non insurance treatment was large. 9. In comparing offered information of medical accidents based on the establishers, general public offered vocabularies, lawyers offered related laws and medical practitioners offered medical knowledge relatively. 10. They all cited the news pressed by the media to offer the current status of domestic medical accidents. Especially among the web sites by general public, NGOs provided the plentiful statistical data related to medical accidents. 11. The web sites that collect the medical accidents were only two. As a result of our research, we found out that, in the flood of information, medical disputes can be occurred by the wrong information from third party, and the medical practitioners have the most passive attitudes on the medical accidents. Thus, it is crucial to have the mutual interchange and exchange of information between lawyer, patients and medical practitioners, so that based on clear mutual comprehension we can solve the accidents and disputes more positively and actively.

• Tuberculosis and Respiratory Diseases
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• v.47 no.6
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• pp.775-785
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• 1999

Background : Though surgery plays an important role in the management of patients with Mycobacterium tuberculosis infection, there is little information regarding the timing of resection. We tried to find out the ideal timing of operation. Method: A retrospective review was performed in 69 patients underwent pulmonary resection for pulmonary tuberculosis between January 1993 and December 1997. They were categorized into various groups according to the length of preoperative specific drug therapy. The rates of treatment failure, realpse and complication in each group were compared statistically by $x^2$-test. Results: Eighty one point two percent were men and 18.8 % women with a median age of 33 years(range, 16 to 63 years). The mean number of resistant drugs was 3.l(range, 0 to 9). Patients were treated preoperatively with multidrug regimens, which mean number of preoperative specific drugs was 4.6, in an effort to reduce the mycobacterial burden with the mean length of preoperative drug therapy, 5.0 months. Postoperative treatment was conducted for a mean period of 13.0 months with a mean number of postoperative specific drugs, 4.4. Postoperative treatment failures were confirmed in 8 among 69 patients(11.6%). 2 of these 8 patients were showed up in the preoperative 3 to 4 months medication group and each of the rest was occurred in the preoperative 2 to 3, 5 to 6, 6 to 7, 12 to 13, 17 to 18 months, less than one month medication group, respectively. 59 of 69 patients were available for evaluation of the relapse rate with the mean duration of the postoperative follow-up, 19.8 months. In 4 patients bacterial relapse was confirmed(6.8%). Each of these 4 was in the preoperative 1 to 2, 2 to 3, 3 to 4, 5 to 6 months medication group. Categorized into various groups according to the length of preoperative specific therapy, there were no statistical significances of the treatment failure rate, relapse rate and complication rate in the groups. There were seven treatment failures of 28 who were AFB culture positive until the time of operation(25%, p<0.01). Categorized the preoperative AFB culture positive group into various groups according to the length of preoperative drug therapy, there were no statistical significances, either. Conclusion: We believe that operation plays an important ancillary role in the treatment of pulmonary tuberculosis. Our results indicate that the timing of resection according to the length of preoperative drug therapy may not cause trouble.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.137-148
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• 2014

Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used