Hyoun-Joong Kong

As the number of robotic surgery procedures has increased, so has the importance of evaluating surgical skills in these techniques. It is difficult, however, to automatically and quantitatively evaluate surgical skills during robotic surgery, as these skills are primarily associated with the movement of surgical instruments. This study proposes a deep learning-based surgical instrument tracking algorithm to evaluate surgeons’ skills in performing procedures by robotic surgery. This method overca

BACKGROUND: Federated learning is a decentralized approach to machine learning; it is a training strategy that overcomes medical data privacy regulations and generalizes deep learning algorithms. Federated learning mitigates many systemic privacy risks by sharing only the model and parameters for training, without the need to export existing medical data sets. In this study, we performed ultrasound image analysis using federated learning to predict whether thyroid nodules were benign or malignan

The findings indicate that prolonged exercise is superior to multiple short sessions for improving the risk of metabolic syndrome and the atherogenic index in middle-aged obese women. However, multiple short sessions can be recommended as an alternative to prolonged exercise when the goal is to decrease blood glucose or waist circumference.

OBJECTIVES: The purpose of this study was to explore new ways of creating value in the medical field and to derive recommendations for the role of medical institutions and the government. METHODS: In this paper, based on expert discussion, we classified Internet of Things (IoT) technologies into four categories according to the type of information they collect (location, environmental parameters, energy consumption, and biometrics), and investigated examples of application. RESULTS: Biometric Io

본 연구는 유헬스 기반의 스마트홈 기술에 운동서비스의 개념을 더한 헬스케어 스마트홈 운동프로그램이 비만 여성 노인의 대사증후군 위험요인에 미치는 효과를 알아보는 데 목적이 있다. 연구대상자는 서울시 K구의 영구임대주택단지에 거주하는 체지방률 30%이상의 비만 여성 노인 중 헬스케어 스마트홈 서비스에 참여를 희망하는 자로 운동군 21명(77.19±6.94세), 통제군 13명(74.08±6.73세)으로 분류하였다. 헬스케어 스마트홈 운동프로그램은 유산소운동과 저항운동의 복합운동 형태로 12주 동안 하루 30~50분, 주당 3회로 실시하였고, 운동전후 대사증후군 위험요인을 측정하였다. 검사결과에 대한 운동효과 분석을 위해 각 변인별로 이원 반복측정 분산분석(repeated measures two-way ANOVA)을 실시하였으며 통계학적 유의수준은 α=.05로 하였다. 12주간의 헬스케어 스마트홈 운동프로그램 실시 후, 대사증후군 위험요인 중 허리둘레(p=.034)에서 사전사후 시기 및

Thus far, there have been no reported specific rules for systematically determining the appropriate augmented sample size to optimize model performance when conducting data augmentation. In this paper, we report on the feasibility of synthetic data augmentation using generative adversarial networks (GAN) by proposing an automation pipeline to find the optimal multiple of data augmentation to achieve the best deep learning-based diagnostic performance in a limited dataset. We used Waters' view ra

BACKGROUND: Alzheimer's disease (AD) is the most common form of dementia, which makes the lives of patients and their families difficult for various reasons. Therefore, early detection of AD is crucial to alleviating the symptoms through medication and treatment. OBJECTIVE: Given that AD strongly induces language disorders, this study aims to detect AD rapidly by analyzing the language characteristics. MATERIALS AND METHODS: The mini-mental state examination for dementia screening (MMSE-DS), whi

Recognizing anatomical sections during colonoscopy is crucial for diagnosing colonic diseases and generating accurate reports. While recent studies have endeavored to identify anatomical regions of the colon using deep learning, the deformable anatomical characteristics of the colon pose challenges for establishing a reliable localization system. This study presents a system utilizing 100 colonoscopy videos, combining density clustering and deep learning. Cascaded CNN models are employed to esti

Stereo disc photograph was analyzed and reconstructed as 3 dimensional contour image to evaluate the status of the optic nerve head for the early detection of glaucoma and the evaluation of the efficacy of treatment. Stepwise preprocessing was introduced to detect the edge of the optic nerve head and retinal vessels and reduce noises. Paired images were registered by power cepstrum method and zero-mean normalized cross-correlation. After Gaussian blurring, median filter application and disparity

Although there are some limitations to our study, these results may prove useful for detecting teeth with impaired vitality and non-invasively differentiating between necrotic and vital pulp.

There is an increasing demand and need for patients and caregivers to actively participate in the treatment process. However, when there are unexpected findings during pediatrics surgery, access restrictions in the operating room may lead to a lack of understanding of the medical condition, as the caregivers are forced to indirectly hear about it. To overcome this, we designed a tele-consent system that operates through a specially constructed mixed reality (MR) environment during surgery. We en

BACKGROUND: Pediatric hemato-oncologic patients require central catheters for chemotherapy, and the junction of the superior vena cava and right atrium is considered the ideal location for catheter tips. Skin landmarks or fluoroscopic supports have been applied to identify the cavoatrial junction; however, none has been recognized as the gold standard. Therefore, we aim to develop a safe and accurate technique using augmented reality technology for the location of the cavoatrial junction in pedi