• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.1151-1152
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• 2019

발달 장애는 신체 및 정신이 해당하는 나이에 맞게 발달하지 않은 상태로, 다른 아동에 비해 신경정신과적 질환 발생 확률이 높기 때문에 발달장애 아동의 치료는 매우 중요하다. 그러나 주관적 판단에 의해 이루어지는 기존 작업치료의 경우, 정량적 성과 지표를 확인하기 힘들고 대상자 스스로 지속적으로 진행하기에 한계가 있다. 본 연구에서는 치료 모델을 가상 공간상에 구현하여 공간에 구애받지 않고 치료를 진행할 수 있으며, 수행 결과에 대한 자료를 정확하고 지속적으로 기록하며 확인할 수 있도록 하였다. 또한, AI 스피커를 통해 치료에 대한 피드백을 줌으로써, 대상자 스스로 실시하여 치료자의 개입을 줄여 심리적 부담을 덜어 더욱 정확한 수행이 이루어지도록 하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.928-930
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• 2020

본 논문은 인공지능 플랫폼 기반의 요로결석 진단을 위한 CT 영상 데이터 자동판독 시스템에 대해 기술하고자 한다. 제안한 시스템은 웹 기반의 플랫폼을 기반으로 하며, 인공지능 기반의 진단 알고리즘을 장착하여 빠르게 요로결석 환자의 스크리닝에 목적을 두고 있다. 병원정보시스템의 PACS와 EMR과 연계와 Deep learning 진단 알고리즘을 적용한 요로결석 자동판독 시스템을 개발하였다. 특히, 기 구축된 인공지능 플랫폼을 통해 추출한 데이터셋을 기반으로 진단 알고리즘 개발 방법과 수행 결과를 보인다. 제안한 시스템은 요로결석 진단과 수술여부에 의사결정지원 시스템으로 임상에서 활용될 것으로 기대하고 있다.

• Korean Journal of Radiology
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• v.25 no.6
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• pp.518-539
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• 2024

Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool for diagnosing and risk-stratifying patients with suspected coronary artery disease (CAD). Recent advancements in image analysis and artificial intelligence (AI) techniques have enabled the comprehensive quantitative analysis of coronary atherosclerosis. Fully quantitative assessments of coronary stenosis and lumen attenuation have improved the accuracy of assessing stenosis severity and predicting hemodynamically significant lesions. In addition to stenosis evaluation, quantitative plaque analysis plays a crucial role in predicting and monitoring CAD progression. Studies have demonstrated that the quantitative assessment of plaque subtypes based on CT attenuation provides a nuanced understanding of plaque characteristics and their association with cardiovascular events. Quantitative analysis of serial CCTA scans offers a unique perspective on the impact of medical therapies on plaque modification. However, challenges such as time-intensive analyses and variability in software platforms still need to be addressed for broader clinical implementation. The paradigm of CCTA has shifted towards comprehensive quantitative plaque analysis facilitated by technological advancements. As these methods continue to evolve, their integration into routine clinical practice has the potential to enhance risk assessment and guide individualized patient management. This article reviews the evolving landscape of quantitative plaque analysis in CCTA and explores its applications and limitations.

• Journal of Internet of Things and Convergence
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• v.6 no.2
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• pp.65-72
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• 2020

The study aims to measure and analysis the spatial equity of Medical welfare facilities for older persons and services, and, based on this, to seek the plan to secure the fairness. To this end, the research was carried out by converging the studies of geography and regional development for the equity of social welfare studies and space arrangement on types and functions of Medical welfare facilities for older persons. The main results of the study showed that, first, in case of the spatial arrangement(desire-to-service), Medical welfare facilities for older persons are located in all areas of cities(Si) and counties(Gun) but mostly existing in cities. Second, in case of the equity of regional distribution of Medical welfare facilities for older persons, it can say the equity in Gun is higher than Si, comparing the regions of Si and Gun. Third, in case of spatial equity of sanatorium for older persons, the spatial equity of care facilities for older persons showed statistical difference depending on the time required to reach the facility, but no difference on distance. This study made various suggestions based on the results of the above research, and suggested the necessity of convergence studies grafting technologies such as AI and the Internet of Things.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.7
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• pp.3191-3194
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• 2014

Adenocarcinoma of lung has high incidence and a poor prognosis, woith chemotherapy as the main therapeutic tool, most commonly with cisplatin. However, chemotherapy resistance develops in the majority of patients during clinic treatment. Mechanisms of resistance are complex and still unclear. Although annexin play important roles in various tumor resistance mechanisms, their actions in cisplatin-resistant lung adenocarcinoma remain unclear. Preliminary studies by our group found that in cisplatin-resistant lung cancer A549 cells and lung adenocarcinoma tissues, both mRNA and protein expression of annexins A1, A2 and A3 is increased. Using a library of annexin A1, A2 and A3 targeting combined molecules already established by ourselves we found that specific targeting decreased cisplatin-resistance. Taken together, the underlined effects of annexins A1, A2 and A3 on drug resistance and suggest molecular mechanisms in cisplatin-resistant A549 cells both in vivo and in vitro. Furthermore, the study points to improved research on occurrence and development of lung adenocarcinoma, with provision of effective targets and programmes for lung adenocarcinoma therapy in the clinic.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.11
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• pp.5409-5413
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• 2012

At present, multiple myeloma (MM) remains an incurable disease and cologenic cells may be responsible for disease relapse. It has been proposed that CD20+/CD138- NCI-H929 cells could be hallmarks of MM clonogenic cells. Here, the immunology phenotype of NCI-H929 cells is described. Only a small population of CD20+/CD138- cells (<1%) was found in the NCI-H929 cell line, but CD20+/CD138- cells were not detected. We found that CD20+/CD138+ cells were able to exhibit cologenic capacity by colony formation assay and continuous passage culture. Proteins were analyzed by 1D-SDS-PAGE and TMT based quantitative differential liquid chromatography tandem mass spectrometry (LC-MS/MS). 1,082 non-redundant proteins were identified, 658 of which were differentially expressed with at least a 1.5-fold difference. 205 proteins in CD20+ cells were expressed at higher levels and 453 proteins were at lower levels compared with CD20- cells. Most proteins had catalytic and binding activity and mainly participated in metabolic processes, cell communication and molecular transport. These results proved that there are different biological features and protein expression profile between CD20+ and CD20- cells in the NCI-H929 cell line.

• BMB Reports
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• v.46 no.3
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• pp.163-168
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• 2013

The AML1 gene is an essential transcription factor regulating the differentiation of hematopoietic stem cells into mature blood cells. Though at least 12 different alternatively spliced AML1 mRNAs are generated, three splice variants (AML1a, AML1b and AML1c) have been characterized. Here, using the reverse transcription-polymerase chain reaction with outward-facing primers, we identified a novel non-polyadenylated transcript from the AML1 gene, with exons 5 and 6 scrambled. The novel transcript resisted RNase R digestion, indicating it is a circular RNA structure that may originate from products of mRNA alternative splicing. The expression of the novel transcript in different cells or cell lines of human and a number of other species matched those of the canonical transcripts. The discovery provides additional evidence that circular RNA could stably exist in vivo in human, and may also help to understand the mechanism of the regulation of the AML1 gene transcription.

• Journal of Convergence Korean Medicine
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• v.6 no.1
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• pp.37-42
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• 2024

Objectives: This study aims to evaluate the clinical validity of the system by conducting a clinical study to assess the diagnostic agreement between the system and Korean medical doctors. Methods: This study was conducted from September 7, 2023, to December 7, 2023, across five Korean medicine institutions, involving 100 adult participants aged 20-64 who consented to participate. Participants first entered their symptoms into a web-based program, which utilized an AI-based algorithm to diagnose 36 types of pattern differentiation. Subsequently, Korean medical doctors conducted face-to-face diagnoses using the same 36 types. The diagnostic agreement between the system and the doctors' diagnoses was analyzed using descriptive statistical analysis, and the results were expressed as a percentage agreement. Results: Analysis of the diagnostic data from 100 participants revealed that the web-based diagnosis support system identified an average of 7.76±0.79 patterns per patient, while Korean medical doctors identified an average of 7.99±0.10 patterns per patient. The diagnostic agreement between the system and the doctors showed an average of 7.08±1.08 patterns per patient, with an overall diagnostic agreement rate of 88.57±13.31%. Conclusion: This study developed a web-based diagnosis support system for traditional Korean medicine and evaluated its clinical validity by assessing diagnostic agreement. Comparing the diagnoses of the system with those of Korean medical doctors for 100 patients, the system showed an approximately 89% agreement rate with the clinical diagnoses. The system holds potential for aiding Korean medical doctors in pattern differentiation diagnosis in clinical practice.

• Korean Journal of Artificial Intelligence
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• v.5 no.1
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• pp.1-9
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• 2017

Recently, the Q-Learning algorithm, which is one kind of reinforcement learning, is mainly used to implement artificial intelligence system in combination with deep learning. Many research is going on to improve the performance of Q-Learning. Therefore, purpose of theory try to improve the performance of Q-Learning algorithm. This Theory apply Cross Entropy Error to the loss function of Q-Learning algorithm. Since the mean squared error used in Q-Learning is difficult to measure the exact error rate, the Cross Entropy Error, known to be highly accurate, is applied to the loss function. Experimental results show that the success rate of the Mean Squared Error used in the existing reinforcement learning was about 12% and the Cross Entropy Error used in the deep learning was about 36%. The success rate was shown.

• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.74-81
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• 2017

Recently, there are many companies that use systems based on artificial intelligence. The accuracy of artificial intelligence depends on the amount of learning data and the appropriate algorithm. However, it is not easy to obtain learning data with a large number of entity. Less data set have large generalization errors due to overfitting. In order to minimize this generalization error, this study proposed DGA(Dropout Genetic Algorithm) which can expect relatively high accuracy even though data with a less data set is applied to machine learning based genetic algorithm to deep learning based dropout. The idea of this paper is to determine the active state of the nodes. Using Gradient about loss function, A new fitness function is defined. Proposed Algorithm DGA is supplementing stochastic inconsistency about Dropout. Also DGA solved problem by the complexity of the fitness function and expression range of the model about Genetic Algorithm As a result of experiments using MNIST data proposed algorithm accuracy is 75.3%. Using only Dropout algorithm accuracy is 41.4%. It is shown that DGA is better than using only dropout.