• Radiation Oncology Journal
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• v.28 no.2
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• pp.64-70
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• 2010

Purpose: The aim of the present study was to retrospectively evaluate the incidence of hypothyroidism in locally advanced head and neck cancer patients who received radiotherapy (RT) either with or without neck dissection. Materials and Methods: From January 2000 to December 2005, 115 patients with locally advanced head and neck cancer and who received definitive RT or postoperative RT including standard anterior low-neck field were recruited to be part of this study. Nineteen patients had undergone ipsilateral neck dissection, whereas, 18 patients underwent bilateral neck dissection, and 78 patients were received RT alone. Patients' ages ranged from 28 to 85 years (median, 59 years) and there were a total of 73 male and 42 female patients. The primary tumor sites were the oral cavity, oropharynx, hypopharynx, larynx, and other sites in 18, 40, 28, 22 and 7 patients, respectively. Radiation dose to the thyroid gland ranged from 44 Gy to 66 Gy with a median dose of 50 Gy. Follow-up time ranged from 2 to 91 months, with a median of 29 months. Results: The 1- and 3- year incidence of hypothyroidism was 28.7% (33 patients) and 33.0% (38 patients), respectively. The median time to detection of hypothyroidism was 8.5 months (range, 0 to 36 months). A univariate analysis revealed that neck node dissection was a risk factor for hypothyroidism (p=0.037). However, no factor was statistically significant from the results of a multivariate analysis. Conclusion: Patients treated for advanced head and neck cancer with radiotherapy with or without neck dissection will develop hypothyroidism. It is important to check the thyroid function periodically in these patientsespecially with the risk factor of neck node dissection.

• Radiation Oncology Journal
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• v.28 no.2
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• pp.71-78
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• 2010

Purpose: To evaluate the result of neoadjuvant chemotherapy, surgery, and radiation therapy in locally advanced breast cancer as well as analyze the prognostic factors affecting survival. Materials and Methods: One hundred fifty-nine patients with breast cancer were treated by neoadjuvant chemotherapy between April 1995 and November 2006 at the Samsung Medical Center. Among these patients, we retrospectively reviewed 105 patients treated with neoadjuvant chemotherapy followed by surgery and radiation therapy for a cure with an initial tumor size >5 cm or clinically positive lymph nodes. All patients received anthracycline based chemotherapy except for 2 patients. According to clinical tumor stage, 3 patients (3%) were cT1, 26 (25%) were cT2, 39 (37%) were T3 and 37 (35%) were T4. Initially, 98 patients (93%) showed axillary lymph node metastasis. The follow-up periods ranged from 7~142 months (median, 41 months) after the beginning of neoadjuvant chemotherapy. Results: Locoregional failure free survival rate and distant metastasis free survival rate at 5 years were 82.1% and 69.9%, respectively. Disease free survival rate and overall survival rate at 5 years were 66.1% and 77.1%, respectively. The results of a univariate analysis indicate that clinical tumor stage, pathologic tumor stage, pathologic nodal stage and pathologic TNM stage were statistically significant factors for disease free survival rate and overall survival rate. Whereas, a multivariate analysis indicated that only hormone therapy was a statistically significant factor for survival. Conclusion: The current study results were comparable to other published studies for neoadjuvant chemotherapy for breast cancer. Hormone therapy was a statistically significant prognostic factor. The patients with early clinical or pathologic stage had a tendency to improve their survival rate.

• Radiation Oncology Journal
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• v.29 no.1
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• pp.20-27
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• 2011

Purpose: This study was designed to evaluate the results of local control, survival rate, prognostic factors, and failure pattern in locally advanced esophageal cancer. Materials and Methods: We retrospectively studied 50 patients with locally advanced esophageal cancer treated with concurrent chemoradiotherapy at Keimyung University Dongsan Medical Center from June of 1999 to August of 2008. Seven patients with inappropriate data were excluded, and 43 patients were analyzed. There were 39 males and four female patients ranging in age from 43 to 78 years (median, 63 years). There were seven patients with stage IIA and 36 with stage III. Irradiation from 46 Gy to 63 Gy (median, 54 Gy) was carried out 5 days per week, 1.8 Gy once a day. There were eight patients with neo-adjuvant chemotherapy, and we mostly used 5-fluorouracil, cisplatin with 3 cycles for concurrent chemotherapy. The range of follow up periods was from 2 to 82 months (median, 15.5). Results: There were nine patients that exhibited a cornplete response, 23 that exhibited a partial response, 9 that exhibited no response, and 2 that exhibited disease progression. The median survival time was 15 months. Two-year and 5-year survival rates were 36.5% and 17.3%, respectively. Two-year and 5-year disease-free survival rates were 32.4% and 16%, respectively. Treatment failure occurred in 22 patients (51.2%). Patterns of failure were categorized as local failure in 18 patients and distant metastasis in four patients. In a univariate analysis for prognostic factors related to overall survival and disease-free survival, the hemoglobin levels during chemoradiotherapy (${\geq}$ 12 vs. <12, p=0.02(p=0.1) and the response to the treatments (CR/PR vs. NR/PD, p=0.002/p< 0.0001) were statistically significant. In a multivariate analysis, only response to the treatments was revealed to be statistically significant. There was no statistical significance associated with patient age, gender, disease stage, T-stage, smoking history, tumor location, or neo-adjuvant chemotherapy. Conclusion: Our survival rate was similar to those of other institutions. Local recurrence was the main reason for failure. It is suggested that further prospective studies should be performed to improve local control.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.1
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• pp.50-57
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• 2016

This study was conducted to determine the effect of mathematical transformation on near infrared spectroscopy (NIRS) calibrations for the prediction of chemical composition and fermentation parameters in corn silage. Corn silage samples (n=407) were collected from cattle farms and feed companies in Korea between 2014 and 2015. Samples of silage were scanned at 1 nm intervals over the wavelength range of 680~2,500 nm. The optical data were recorded as log 1/Reflectance (log 1/R) and scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with several spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation ($R^2{_{cv}}$) and the lowest standard error of cross validation (SECV). Results of this study revealed that the NIRS method could be used to predict chemical constituents accurately (correlation coefficient of cross validation, $R^2{_{cv}}$, ranging from 0.77 to 0.91). The best mathematical treatment for moisture and crude protein (CP) was first-order derivatives (1, 16, 16, and 1, 4, 4), whereas the best mathematical treatment for neutral detergent fiber (NDF) and acid detergent fiber (ADF) was 2, 16, 16. The calibration models for fermentation parameters had lower predictive accuracy than chemical constituents. However, pH and lactic acids were predicted with considerable accuracy ($R^2{_{cv}}$ 0.74 to 0.77). The best mathematical treatment for them was 1, 8, 8 and 2, 16, 16, respectively. Results of this experiment demonstrate that it is possible to use NIRS method to predict the chemical composition and fermentation quality of fresh corn silages as a routine analysis method for feeding value evaluation to give advice to farmers.

• Journal of Nutrition and Health
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• v.47 no.2
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• pp.113-123
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• 2014

Purpose: Vitamin D has been known to play an important role in the central nervous system and brain functions in the human body, and cumulative evidence has shown that vitamin D deficiency might be linked with various mental health conditions. Epidemiologic studies have shown that vitamin D deficiency may be associated with higher risk of depression in the US and European populations. However, limited information is available regarding the association between vitamin D status and depression in the Korean population. The objective of this study was to examine the associations between vitamin D levels and prevalence of depression. Methods: We conducted a cross-sectional analysis using nationally representative data from the 2008-2010 Korean National Health and Nutrition Examination Survey from which serum 25-hydroxyvitamin D concentrations were available. A total of 18,735 adults who had available demographic, dietary, and lifestyle information were included in our analysis. We defined "depression" with a diagnosis by a physician. "Depressed condition" was defined as having feelings of sadness or depression without diagnosis by a physician. Results: The prevalence of depression was 1.63% and 5.43% in Korean men and women, respectively; 12.5% of men and 26.1% of women were defined as the group having depressed conditions. In multivariate logistic regression models, no significant associations were observed between vitamin D status and prevalence of depression or depressed conditions in Korean men and women. Conclusion: We found no association between vitamin D insufficiency and depression/depressed conditions in Korean adults. Future large prospective studies and randomized controlled trials are needed to confirm this relationship.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.2
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• pp.114-120
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• 2019

This study was carried out to explore the accuracy of near infrared spectroscopy(NIRS) for the prediction of moisture content and chemical parameters on winter annual forage crops. A population of 2454 winter annual forages representing a wide range in chemical parameters was used in this study. Samples of forage were scanned at 1nm intervals over the wavelength range 680-2500nm and the optical data was recorded as log 1/Reflectance(log 1/R), which scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares(PLS) multivariate analysis in conjunction with spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation($R^2$) and the lowest standard error of cross-validation(SECV). The results of this study showed that NIRS calibration model to predict the moisture contents and chemical parameters had very high degree of accuracy except for barely. The $R^2$ and SECV for integrated winter annual forages calibration were 0.99(SECV 1.59%) for moisture, 0.89(SECV 1.15%) for acid detergent fiber, 0.86(SECV 1.43%) for neutral detergent fiber, 0.93(SECV 0.61%) for crude protein, 0.90(SECV 0.45%) for crude ash, and 0.82(SECV 3.76%) for relative feed value on a dry matter(%), respectively. Results of this experiment showed the possibility of NIRS method to predict the moisture and chemical composition of winter annual forage for routine analysis method to evaluate the feed value.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of the Korean Orthopaedic Association
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• v.55 no.6
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• pp.487-494
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• 2020

Purpose: No attempt has been made to identify the relationship between the study characteristics and citation rates of articles published in the Journal of the Korean Orthopaedic Association (JKOA). This study classified the study characteristics of articles in the JKOA and analyzed the relationship between the study characteristics and citation rates. Materials and Methods: A cohort study was conducted on all articles published from February 2001 to December 2015. Three independent reviewers classified the articles according to the article type, material, time of the study, design, clinical categories, number of authors, and number of cases. The citation numbers of each article by other journals were taken in January 2020. Univariate analyses were conducted to assess the effect of each characteristic, and multivariate linear regression analysis was performed to analyze the overall relationship between the characteristics and the citation rates. Results: A total of 1,640 articles were published from 2001 to 2015, and 724 articles were cited more than once. The articles published in 2009 had the highest average number of citations. Original articles had the highest citation rates, followed in descending order by surgical techniques and reviews, instructional course lectures, and case reports (p<0.001). Among the case reports, articles dealing with general trauma scored significantly higher average citations (mean=1.5, p=0.006). Among the original articles, articles on general orthopedics had the highest citation rates, followed in order by clinical articles and experimental articles. Among the clinical articles, epidemiologic studies (mean=5.0, p<0.001) and studies on the spine (mean=1.7, p<0.001) recorded significantly higher citation rates than the others. Conclusion: Of all the articles published in the JKOA from 2001 to 2015, articles dealing with general trauma had the highest citation rates among case reports. Among the original articles, epidemiologic studies and studies concerning the spine were cited significantly more than others.

• Journal of the Korean Orthopaedic Association
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• v.56 no.5
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• pp.404-412
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• 2021

Purpose: This study examined the degree of cartilage regeneration by performing second-look arthroscopy in a group of patients who underwent high tibial osteotomy and microfractures for unicompartmental osteoarthritis of the medial knee joint and to determine the factors affecting cartilage regeneration. In addition, this study analyzed whether there is a relationship between the degree of cartilage regeneration and functional results. Materials and Methods: From 2007 to 2015, this study evaluated 81 cases who underwent second-look arthroscopy at the time of plate removal after a microfracture and high tibial osteotomy with a minimum two-year follow-up. The degree of femoral cartilage injury before surgery was classified by ICRS (International Cartilage Research Society), and all were grade III and IV. After second-look arthroscopy, cartilage regeneration was classified into a well-regenerated group (grade I, II) and a poorly regenerated group (grade III, IV). The independent factors influencing cartilage regeneration were identified through multivariate logistic regression analysis. In addition, the functional results were compared before and after surgery between the two groups using the Knee Society score (KSS) and the Western Ontario and McMaster Universities Osteoarthritis Index score (WOMAC). Results: Age, sex, body mass index, postoperative radiologic factors, and preoperative joint condition did not affect the degree of cartilage regeneration significantly. The large cartilage defect (≥2.0 cm²) (p=0.011) and the presence of kissing lesions (p=0.027) were associated with poor cartilage regeneration. No significant difference in the KSS and WOMAC scores was observed between the group with good and poor cartilage regeneration. Conclusion: The presence of a large cartilage defect and kissing lesions is associated with poor cartilage regeneration after high tibial osteotomy and microfracture. On the other hand, the degree of the regenerated cartilage did not show any correlation with the functional outcome.

• Journal of the Korean Orthopaedic Association
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• v.56 no.1
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• pp.61-67
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• 2021

Purpose: To evaluate the prognostic factors affecting poor functional outcomes in patients with retear after rotator cuff repair. Materials and Methods: From January 2013 to December 2018, among 631 patients who underwent arthroscopic repair of a rotator cuff tear, 42 patients, who could be followed-up for more than one year and showed a retear of the repaired cuff on magnetic resonance imaging (MRI), were collected retrospectively. The preoperative demographic data, range of motion, American Shoulder and Elbow Surgeons (ASES) score, fatty degeneration, and tear progression on postoperative MRI, as well as other factors that could affect the clinical outcomes, were analyzed. Patients who scored <80 points on the ASES score were allocated to the poor function group. The risk factors for poor clinical outcomes were compared with the group with ASES scores of 80 or above. Results: The postoperative functional results in the group with retear (n=42) after arthroscopic rotator cuff repair showed significant improvement. Univariate analysis revealed the preoperative visual analogue scale (VAS) score and tear progression to have associations with a poor shoulder function. In addition, subscapularis repair was found to be associated with a good shoulder function. The preoperative VAS score and tear progression except for subscapularis repair were independent factors associated with poor clinical outcomes according to multivariate logistic regression analysis. Conclusion: In patients with retear after rotator cuff repair, the preoperative VAS and tear progression in postoperative MRI are factors predicting a poor functional outcome.