• Korean Journal of Clinical Pharmacy
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• v.16 no.1
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• pp.9-13
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• 2006

Patient counseling is emerging as one of the most important roles of community pharmacists because the information on the standard labeling for the prescription drug is not sufficient to ensure the correct use of the drug. However, excessive workload of the community pharmacists in Korea discourages the provision of the effective patient counseling. The use of auxiliary label may be an efficient tool to help patients correctly use the prescription drug in this situation. As a preliminary study to encourage the use of auxiliary label, we have performed a survey analysis of familiarity and willingness of community pharmacists to use the auxiliary label. About three quarters of the participating community pharmacists have heard of the auxiliary label, however, there was not a single pharmacist who uses the label. Furthermore, only one fifth of the participating pharmacists were willing to use the label if they have to purchase. Therefore, it is recommended that governmental and non-profit organizations such as Korean Pharmaceutical Association educate community pharmacists regarding usefulness of the auxiliary label with focus on enhancing patient compliance and constrainment of healthcare expense.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.29-30
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• 2022

Curriculum learning은 딥러닝의 성능을 향상시키기 위해 사람의 학습 과정과 유사하게 일종의 'curriculum'을 도입해 모델을 학습시키는 방법이다. 대부분의 연구는 학습 데이터 중 개별 샘플의 난이도를 기반으로 점진적으로 모델을 학습시키는 방안에 중점을 두고 있다. 그러나, coarse-to-fine 메카니즘은 데이터의 난이도보다 학습에 사용되는 class의 유사도가 더욱 중요하다고 주장하며, 여러 난이도의 auxiliary task를 차례로 학습하는 방법을 제안했다. 그러나, 이 방법은 혼동행렬 기반으로 class의 유사성을 판단해 auxiliary task를 생성함으로 다중 레이블 분류에는 적용하기 어렵다는 한계점이 있다. 따라서, 본 논문에서는 multi-label 환경에서 multi-class와 binary task를 생성하는 방법을 제안해 coarse-to-fine 메카니즘 적용을 위한 방안을 제시하고, 그 결과를 분석한다.

• International Journal of Contents
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• v.6 no.1
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• pp.6-11
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• 2010

Recently, there has been research to use portable digital camera to recognize objects in natural scene images, including labels or marks on a cylindrical surface. In many cases, text or logo in a label can be distorted by a structural movement of the object on which the label resides. Since the distortion in the label can degrade the performance of object recognition, the label should be rectified or restored from deformations. In this paper, a new method for label detection and restoration in digital images is presented. In the detection phase, the Hough transform is employed to detect two vertical boundaries of the label, and a horizontal edge profile is analyzed to detect upper-side and lower-side boundaries of the label. Then, the biquadratic transformation is used to restore the rectangular shape of the label. The proposed algorithm performs restoration of 3D objects in a 2D space, and it requires neither an auxiliary hardware such as 3D camera to construct 3D models nor a multi-camera to capture objects in different views. Experimental results demonstrate the effectiveness of the proposed method.

• 한국임상약학회:학술대회논문집
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• 2007.12a
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• pp.172-172
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• 2007

• 한국임상약학회:학술대회논문집
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• 2007.12a
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• pp.181-181
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• 2007

• YAKHAK HOEJI
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• v.52 no.3
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• pp.201-211
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• 2008

All pharmacists must provide the drug consultation whenever dispense drugs to patients by the Korean Pharmacy Law. Drug consultation is very important procedure for increasing pharmacotherapy. Because it maximizes the therapeutic effects or/and minimizes adverse drug reaction during the drug therapy. However, it is not easy to do because of the dynamic and hectic pharmacy environment. Especially, if someone has a disabling body function, they required more time and efforts to perform consultation by pharmacist. Currently several auxiliary labels for helping drug consultation are using in pharmacy practice but not for disabling patients. Therefore we developed the total 53 auxiliary labels with size of 0.7 cm (width) and 1 cm (length) by Braillewriter letters for blind patients. This research has been performed for total 12 months (Mar. 15ts, 2007$\sim$Feb. 25th, 2008) and the developing methods are consisted of 4 steps: 1) selection of essential informations, 2) simplification of information, 3) changing for Braillewriter letters, 4) application and revising by blindness patients. Also the labels are consisted of 12 for adverse reactions and precautions, 8 for directions, 2 for storages, 9 for duration, 9 for dosage forms, and 12 for common names. After developed those labels, we revised those labels by discussion with 2 blind people. In conclusion, the new auxiliary labels for blind patients can increase therapeutic effects and decrease risks from pharmacotherapy besides decreasing of pharmacist's work load in the future.

• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.257-268
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• 2011

Machine learning and data mining have found many applications in biological domains, where we look to build predictive models based on labeled training data. However, in practice, high quality labeled data is scarce, and to label new data incurs high costs. Transfer and multitask learning offer an attractive alternative, by allowing useful knowledge to be extracted and transferred from data in auxiliary domains helps counter the lack of data problem in the target domain. In this article, we survey recent advances in transfer and multitask learning for bioinformatics applications. In particular, we survey several key bioinformatics application areas, including sequence classification, gene expression data analysis, biological network reconstruction and biomedical applications.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.185-207
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• 2022

Recently, with the development of deep learning technology, researches to apply a deep learning algorithm to analyze unstructured data such as text and images are being actively conducted. Text classification has been studied for a long time in academia and industry, and various attempts are being performed to utilize data characteristics to improve classification performance. In particular, a hierarchical relationship of labels has been utilized for hierarchical classification. However, the top-down approach mainly used for hierarchical classification has a limitation that misclassification at a higher level blocks the opportunity for correct classification at a lower level. Therefore, in this study, we propose a methodology for classifying hierarchical data using the autoencoder-based deeply supervised network that high-level classification does not block the low-level classification while considering the hierarchical relationship of labels. The proposed methodology adds a main classifier that predicts a low-level label to the autoencoder's latent variable and an auxiliary classifier that predicts a high-level label to the hidden layer of the autoencoder. As a result of experiments on 22,512 academic papers to evaluate the performance of the proposed methodology, it was confirmed that the proposed model showed superior classification accuracy and F1-score compared to the traditional supervised autoencoder and DNN model.

• Korean Journal of Acupuncture
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• v.31 no.1
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• pp.5-13
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• 2014

Objectives : This study aims to evaluate the effectiveness and safety of acupuncture and explore the appropriate number of treatment for postmenopausal women diagnosed with prehypertension and stage 1 hypertension. Methods : A 4-arm randomized open label pilot trial will be performed at 2 centers. Sixty participants will be divided into 2 treatment groups and 2 control groups. Treatment groups will receive acupuncture at 8 points(bilateral GB20, LI11, ST36, SP6) for 4 weeks(treatment group A, 10 total sessions) or 8 weeks(treatment group B, 20 total sessions), while maintaining usual care. Control groups will not receive acupuncture but will be under usual care for 16 weeks(control group C) or 20 weeks(control group D). Each patient's living habits will be corrected and drugs that may affect blood pressure(BP) will be prohibited. Treatment group A and control group C will be evaluated at 4, 8, 12, and 16 weeks after randomization, while treatment group B and control group D will be evaluated at 4, 8, 12, 16, and 20 weeks after randomization. The major outcome variable is the magnitude of change in diastolic BP levels at 4 weeks after randomization; auxiliary outcome variables are (1) diastolic BP change at 8, 16, and 20 weeks, (2) systolic BP change, (3) BP control rate, (4) lipid profiles, and (5) high-sensitivity C-reactive protein. Patient safety will be assessed at every visit. Results and Conclusions : The study findings may help develop evidence for the effectiveness and safety of acupuncture for BP control.