• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2249-2254
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• 2013

The study was conducted to determine the effect of Malaysian jungle Tualang Honey (TH) on development of breast cancer induced by the carcinogen 7,12-dimethylbenz(${\alpha}$)anthracene (DMBA) in rats. Forty nulliparous female Sprague-Dawley rats were given 80 mg/kg DMBA then randomly divided into four groups: Group 1 served as a Control while Groups 2, 3 and 4 received 0.2, 1.0 or 2.0 g/kg bodyweight/day of TH, respectively, for 150 days. Results showed that breast cancers in the TH-treated groups had slower size increment and smaller mean tumor size (${\leq}2cm^3$) compared to Controls (${\leq}8cm^3$). The number of cancers developing in TH-treated groups was also significantly fewer (P<0.05). Histological grading showed majority of TH-treated group cancers to be of grade 1 and 2 compared to grade 3 in controls. There was an increasing trend of apoptotic index (AI) seen in TH-treated groups with increasing dosage of Tualang Honey, however, the mean AI values of all TH-treated groups were not significantly different from the Control value (p>0.05). In conclusion, Tualang Honey exerted positive modulation effects on DMBA-induced breast cancers in rats in this preliminary study.

• Clinical Endoscopy
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• v.57 no.1
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• pp.1-10
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• 2024

Barrett's esophagus (BE) is the precursor to esophageal adenocarcinoma (EAC), and is caused by chronic gastroesophageal reflux. BE can progress over time from metaplasia to dysplasia, and eventually to EAC. EAC is associated with a poor prognosis, often due to advanced disease at the time of diagnosis. However, if BE is diagnosed early, pharmacologic and endoscopic treatments can prevent progression to EAC. The current standard of care for BE surveillance utilizes the Seattle protocol. Unfortunately, a sizable proportion of early EAC and BE-related high-grade dysplasia (HGD) are missed due to poor adherence to the Seattle protocol and sampling errors. New modalities using artificial intelligence (AI) have been proposed to improve the detection of early EAC and BE-related HGD. This review will focus on AI technology and its application to various endoscopic modalities such as high-definition white light endoscopy, narrow-band imaging, and volumetric laser endomicroscopy.

• The Journal of Bigdata
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• v.6 no.2
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• pp.99-108
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• 2021

Recently, unexpected and more advanced cyber medical treat attacks are on the rise. However, in responding to various patterns of cyber medical threat attack, rule-based security methodologies such as physical blocking and replacement of medical devices have the limitations such as lack of the man-power and high cost. As a way to solve the problems, the medical community is also paying attention to artificial intelligence technology that enables security threat detection and prediction by self-learning the past abnormal behaviors. In this study, there has collecting and learning the medical information data from integrated Medical-Information-Systems of the medical center and introduce the research methodology which is to develop the AI-based Net-Working Behavior Adaptive Information data. By doing this study, we will introduce all technological matters of rule-based security programs and discuss strategies to activate artificial intelligence technology in the medical information business with the various restrictions.

• Journal of the Korean Medical Association
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• v.61 no.12
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• pp.765-775
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• 2018

With growing interest in novel digital healthcare devices, such as artificial intelligence (AI) software for medical diagnosis and prediction, and their potential impacts on healthcare, discussions have taken place regarding the regulatory approval, coverage, and clinical implementation of these devices. Despite their potential, 'digital exceptionalism' (i.e., skipping the rigorous clinical validation of such digital tools) is creating significant concerns for patients and healthcare stakeholders. This white paper presents the positions of the Korean Society of Radiology, a leader in medical imaging and digital medicine, on the clinical validation, regulatory approval, coverage decisions, and clinical implementation of novel digital healthcare devices, especially AI software for medical diagnosis and prediction, and explains the scientific principles underlying those positions. Mere regulatory approval by the Food and Drug Administration of Korea, the United States, or other countries should be distinguished from coverage decisions and widespread clinical implementation, as regulatory approval only indicates that a digital tool is allowed for use in patients, not that the device is beneficial or recommended for patient care. Coverage or widespread clinical adoption of AI software tools should require a thorough clinical validation of safety, high accuracy proven by robust external validation, documented benefits for patient outcomes, and cost-effectiveness. The Korean Society of Radiology puts patients first when considering novel digital healthcare tools, and as an impartial professional organization that follows scientific principles and evidence, strives to provide correct information to the public, make reasonable policy suggestions, and build collaborative partnerships with industry and government for the good of our patients.

• Journal of the korean veterinary medical association
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• v.43 no.6
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• pp.536-542
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• 2007

국내뿐만 아니라, 전세계적으로 관심을 가지고 있는 인플루엔자 바이러스(influenza virus)는 일반적으로 고열과 기침을 동반한 독감을 일으키는 원인체로서, 사람을 포함한 포유동물과 조류 등에 감염되고 전염될 수 있기 때문에 많은 문제를 유발 하고 있습니다. 또한 이미 많이 알려진 조류 인플루엔자(avain influenza; AI)의 경우 조류에서 뿐만 아니라, 사람에게 전염될 경우 치명적인 결과를 초래하는 경우가 많아 때로는 공포의 대상이 되기도 합니다. 더욱이 조류 인플루엔자(AI)는 보건상의 문제를 해결하기 위해 많은 노력을 기울이고 있음에도 불구하고, 현재까지도 국내.외 여러 산업에 영향을 주거나 사람이 사망에 까지 이르고 있는 실정입니다. 이러한 현실에서 인플루엔자 바이러스가 사람을 비롯한 여러 동물에서 감염 혹은 전염이 확인될 경우 많은 걱정을 할 수 밖에 없으며, 만약 동물에서의 바이러스 감염 사실이 과장되거나 잘못된 정보가 대중에게 알려질 경우에는 사회적으로 엄청난 파장을 일으킬 수 밖에 없는 것이 현실입니다. 더욱이, 근래 미국에서는 개의 독감(canine flu)이라고 불리는 개의 인플루엔자 바이러스(canine influenza virus; CIV) 감염이 전역으로 확산되고 있는 상황이기 때문에, 국내에서도 예의주시하면서 지켜보고 있을 뿐만 아니라, 수의사를 비롯한 보호자를 개의 인플루엔자 바이러스에 대해서 많은 관심을 가지고 있는 상황입니다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.1013-1015
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• 2022

본 논문은 보이스피싱에 취약한 VoIP와 일반 유선전화 상의 보안을 위해 유선전화의 대화내용을 Google STT API 및 텍스트 자연어 처리를 통해 실시간으로 보이스피싱 위험도를 알 수 있는 모델을 제안했다. 보이스피싱 데이터를 Data Augmentation와 BERT 모델을 활용해 보이스피싱을 예방하는 솔루션을 구상했다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.703-705
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• 2023

본 연구는 대화 중 생체신호 데이터를 활용하여 감정 인식 분야에서 더욱 정확하고 범용성이 높은 인식 기술을 제안한다. 이를 위해, 먼저 대화별 길이에 따른 측정값의 개수를 동일하게 조정하고 효과적인 생체신호 데이터의 조합을 비교 및 분석하기 위해 차원 축소 기법인 T-SNE (T-distributed Stochastic Neighbor Embedding)을 활용하여 감정 라벨의 분포를 확인한다. 또한, AutoML (Automated Machine Learning)을 이용하여 축소된 데이터로 감정을 분류 및 각성도와 긍정도를 예측하여 감정을 가장 잘 인식하는 생체신호 데이터의 조합을 발견한다.

• Journal of Korean Medical classics
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• v.33 no.2
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• pp.77-90
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• 2020

Objectives : To determine the meaning of 'yi(噫)' from verses containing the character in 『Huangdineijing』. Methods : First, examples of the usage of 'yi(噫)' in Huangdineijing were collected and analyzed, followed by examples from the other books of the time when 『Huangdineijing』 was written. Finally the term 'ai' which surfaced in a later period than Huangdineijing to refer to eructation was examined. Results & Conclusions : Based on analysis of the usage of 'yi(噫)' in the 『Huangdineijing』, out of a total of 20 cases, 14 cases could be categorized as referring to eructation, 4 cases were difficult to categorize as eructation, and 2 cases were indeterminable. At the time of publication of 『Huangdineijing』, the character 'yi(噫)' was generally used to refer to eructation when used in a medical context, while in non-medical contexts it referred to sigh, or groan. The appearance of 'ai(噯)' is predicted to be during the Song period, but its appearance did not take away the meaning of eructation from 'yi(噫)' and both were used. Based on the change of meaning of 'yi(噫)', we can determine the approximate time when certain contents of the 『Huangdineijing』 were constructed. In the case of '心爲噫[Heart makes 'yi(噫)']', we can understand it as the pectoral qi leaking through the throat manifesting as a sigh in order to relieve stagnation of the excessiveness of the Heart. In cases of deficiency, when the Stomach function is weak, the body is likely to let out a sigh. The term meaning sighing which is 'taixi(大息)' was understood as symptomatic of problems of the Gallbladder as well as the Heart.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.434-436
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• 2021

의료산업은 진단 및 치료 위주의 기술개발이 진행되어왔다. 최근 의료 빅데이터를 기반으로 진단, 치료 및 재활뿐만 아니라 예방과 예후관리까지 지원하는 의료서비스에 대한 패러다임이 변화되고 있다. 특히, 여러 의료 중심의 플랫폼 기술 가운데 객관적인 진단지표를 가지고 있는 의료영상을 기반으로 인공지능 학습에 적용하여 진단 및 예측을 중심으로 한 플랫폼 개발이 진행되고 있다. 하지만, 인공지능 연구에는 많은 학습 데이터가 요구될 뿐만 아니라 학습에 적용하기 위해서는 데이터 특성에 따른 전처리 기술과 분류 작업에 많은 시간 소요되어 이와 같은 문제점을 해결할 수 있는 방법들이 요구되고 있다. 따라서, 본 논문은 인공지능 학습까지 적용하기 위한 의료영상 데이터에 대한 확장 모델을 개발하여 공통적인 조건에 따라 의료영상 데이터가 표준화되어 변환하며, 자동화 시스템 구조에 따라 데이터가 분류·저장되어 인공지능 학습까지 지원할 수 있는 플랫폼을 제안하고자 한다. 그리고 근감소증 학습데이터 관리 및 적용 결과를 통해 플랫폼의 수행성을 검증하였다. 향후 제안한 플랫폼을 통해 의료데이터에 대한 전처리, 분류, 관리까지 지원함으로써 CDM 확장 표준 의료데이터 플랫폼으로 활용 가능성을 보였다.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.175-180
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• 2020

Through case studies for insurance service marketing using artificial intelligence(AI) in the insurtech industry, it investigated how innovative technologies(artificial intelligence, machine learning etc.) are being used in the insurance ecosystems. In particular, through domestic and international case studies, it was examined by Lemonade's service of insurance contracts and getting the indemnity and AI company's service of calculating the compensation through a medical certificate image based on OCR, which brought disruptive innovations using artificial intelligence. As a result of the case analysis, these services have drastically shortened the lead time of insurance contracts and payment through machine learning using numerous customer data based on artificial intelligence. And accurate and reasonable compensation was calculated in the estimation of indemnity, which has a lot of disputes between customers and insurance companies. It was able to increase customer satisfaction and customer value.