The COVID-19 pandemic's impact on prostate cancer screening and diagnosis in Korea

강병진,Kim Kyung Hwan,하홍구 고신대학교(의대) 고신대학교 의과대학 학술지 2023 고신대학교 의과대학 학술지 Vol.38 No.3

Background: The global coronavirus disease 2019 (COVID-19) pandemic, which started in early 2020, has had multiple impacts on cancer care. This study assessed how the COVID-19 pandemic influenced prostate cancer (PCa) screening and diagnosis in South Korea. Methods: Patients who visited the outpatient clinic at a single institution for PCa evaluation were included in this study and divided into a pre-COVID-19 group and a COVID-19 pandemic group, based on the start of the COVID-19 pandemic and social distancing policies on March 1, 2020. The number of prostate-specific antigen (PSA) tests, patients with elevated PSA levels, and prostate biopsy results were analyzed. Results: In total, 8,926 PSA tests were administered during the COVID-19 pandemic, compared to 15,654 before the pandemic (p<0.05). Of 2,132 patients with high PSA levels, 1,055 (49.5%) received prostate biopsies before the pandemic and 1,077 (50.5%) did so during the COVID-19 pandemic. The COVID-19 pandemic group had a higher detection rate of PC, and increased rates of Gleason scores (GS) 7 and 9–10, while the rate of GS 6 decreased compared to the pre-COVID-19 group (p<0.05). The rate of clinically significant PCa (csPCa) was also higher during the pandemic (p<0.05). In both magnetic resonance imaging-guided and standard biopsies, the GS 6 rate decreased, and the csPCa rate increased during the COVID-19 pandemic (each, p<0.05). Conclusions: During the COVID-19 pandemic, the detection rate of prostate biopsies and the rate of csPCa increased significantly. Thus, PCa was diagnosed at a more advanced state in Korea during the COVID-19 pandemic.

Causal Relationships between the Elderly People's Leisure Activities and Their Self-Esteem, Helplessness, Loneliness, Leisure Satisfaction, Life Satisfaction, and Happiness

강병진,차지원 한국운동재활학회 2010 JER Vol.6 No.4

이자율 옵션을 활용한 가계대출 위험관리의 실효성

강병진 한국리스크관리학회 2009 리스크 管理硏究 Vol.20 No.1

이질적 기대와 옵션투자 수요

강병진 명지대학교(서울캠퍼스) 금융지식연구소 2021 금융지식연구 Vol.19 No.1

This paper derives the risk-neutral probability distributions from the market prices of index options, and then extend the theoretical study of Carr and Madan(2001) to examine how the demand for options of investors with heterogeneous beliefs can be determined. It helps to understand the option returns anomaly and the resulting puzzle of supply-demand imbalance of the index options market, which are difficult to explain with the traditional investment theory assuming a representative agent with a homogeneous expectation. Assuming two groups of investors with different heterogeneous expectations, we observed the following results in the S&P500 index options market from 2004 to 2017. First, each investor group has different expectations in mean, volatility, skewness, and kurtosis of underlying stock index returns, but among them, the mean returns shows the largest difference. Accordingly, the optimal investment strategy of each investor group significantly differs in the aspect of exposure to market risk rather than exposure to volatility. Second, the heterogeneous expectations between each investor groups tend to widen when market uncertainty increases, such as the Global Financial Crisis in 2008 and the European Sovereign Debt Crisis in 2010 and 2011. Finally, even though considering their own different heterogeneous expectations for future stock markets, the performance of each investor group is not better than the simple strategy of buy-and-hold of stock index. 본 연구는 옵션의 시장가격으로부터 위험중립확률분포(risk-neutral probability distribution) 를 추정한 후, Carr and Madan(2001)의 이론연구를 확장하여 이질적 기대(heterogeneous beliefs)를 가진 투자자 집단들의 옵션투자 수요가 어떻게 다를 수 있는지를 분석하였다. 이는 동질적 기대(homogeneous belief)를 가진 대표적 투자자(representative agent)를 가정하는 전통적인 투자이론으로는 설명하기 어려운 지수옵션시장의 수익률 이상현상(anomaly) 및 수급 불균형을 이해하기 위한 단초를 제공해 준다. 서로 다른 이질적 기대를 가지는 두 부류의 투자자 집단을 상정한 후, 2004년부터 2017년까지 S&P500 주가지수옵션시장을 분석한 결과 다음의 사실을 확인하였다. 첫째, 각 투자자 집단이 전망하는 주가지수 수익률 분포는 평균, 변동성, 왜도, 첨도 등에서 모두 차이를 나타내지만, 그 중에서도 특히 평균에서 가장 큰 차이를 보인다. 그에 따라 각 투자자 집단의 최적투자전략도 변동성보다는 시장위험에 대한 익스포저에서 크게 차별화된다. 둘째, 각 투자자 집단 간의 수익률 전망 차이는 2008년 글로벌금융위기, 2010년 1차 유럽재정위기, 2011년 2차 유럽재정위기 등 시장 불확실성이 커지는 시기에 확대되는 경향이 뚜렷이 나타난다. 셋째, 각 투자자 집단의 서로 다른 전망에 기초한 투자성과를 분석한 결과, 주가지수를 단순 보유하는 전략에 비해 위험이 크게 상승하여 위험조정성과는 대체로 더 낮아진다.

구조화 파생상품의 투자 효용 : 자동조기상환형 주가연계증권

강병진 한국재무학회 2016 財務硏究 Vol.29 No.1

리스크 기준 포트폴리오 리밸런싱의 성과

강병진,윤선중 단국대학교 미래산업연구소 2023 산업연구 Vol.47 No.1

This paper examines the effectiveness of a risk-contribution rebalancing strategy in reducing portfolio volatility by maintaining a constant contribution of individual assets to the total risk within the portfolio. The study analyzes a five-asset portfolio consisting of domestic equities, domestic bonds, foreign equities, foreign bonds, and commodities. The empirical results reveal that the risk-contribution rebalancing strategy is effective in reducing volatility when there is a low degree of risk concentration among assets. However, when specific assets exhibit high degree of risk concentration, the risk-contribution rebalancing strategy may not effectively reduce volatility and could even increase it. This finding holds even when the asset class is expanded to include crypto assets or equity sector indices. Therefore, unlike the traditional value-based rebalancing strategies that consistently demonstrate a reduction in volatility, regardless of portfolio characteristics, the use of risk-contribution rebalancing strategies requires a careful consideration of portfolio characteristics. 본 논문은 포트폴리오 내에서 개별 자산들이 전체 리스크에 공헌하는 비중을 일정하게 유지시킴으로써, 특정 자산에 대한 과도한 리스크 노출을 지양하고 포트폴리오의 변동성을 줄이고자 하는 이른바 ‘리스크 기준 리밸런싱(Risk–Contribution Rebalancing)’의 성과를 분석하였다. 국내주식, 국내채권, 해외주식, 해외채권, 원자재 등 5개 자산으로 구성된 포트폴리오를 대상으로 실증분석한 결과, 리스크 기준 리밸런싱은 당초 포트폴리오 내에서 자산들 간 리스크 편중도가 약할 경우에는 변동성 완화에 효과적이지만, 그렇지 않을 경우에는 변동성 완화 효과가 미미하거나 오히려 변동성을 확대시킬 수 있음을 확인하였다. 이러한 사실은 포트폴리오를 구성하고 있는 자산 종류를 가상자산(crypto asset) 또는 주식 섹터(sector)별 지수로 확장한 경우에도 여전히 강건하게 유효함을 확인하였다. 따라서 포트폴리오의 특성과 무관하게 변동성 완화 효과가 일관되게 나타나는 전통적인 리밸런싱 기법과는 달리, ‘리스크 기준 리밸런싱’을 적용할 때에는 포트폴리오 특성에 대한 고려가 반드시 선행되어야 한다.

금속성 첨가 Gas를 이용한 High Aspect Ratio Contact 공정 개선

강병진,탁현우,김성배,강지은,염근영 한국표면공학회 2023 한국표면공학회 학술발표회 초록집 Vol.2023 No.5

RGB 채널 영상을 이용한 YOLO 모델 기반의 MWIR 영상 탐지 성능평가

강병진,배재현,김대현,백경훈 제어·로봇·시스템학회 2023 제어·로봇·시스템학회 논문지 Vol.29 No.10

Recently, artificial intelligence is being used in many business fields. In the field of image, it is used in many different forms, starting with simple object detection, tracking, synthetic image generation, and style conversion. In particular, the object detection field has already been applied and used in many fields such as national defense, product defect detection, and security thanks to tremendous development. However, current object detection models are mainly performed with RGB images. Due to this direction of research, a separate study is underway for a model for IR image. Because of this, the development of deep learning models for IR images is much slower than RGB images. In addition, due to the lack of IR image data, research on IR image deep learning models is becoming more and more laggy compared to other deep learning studies. This paper proposes that the model trained on RGB images shows excellent performance in IR images. The object detection deep learning model learns shape information by using feature extraction. Our results show that IR images showing the shape of an object and images learned as RGB images can be sufficiently inferred. As a result, the model trained with RGB images shows robustness even in IR images.

초분광 이미지 기술 및 최신 딥러닝 응용 동향

강병진,김성호,신정섭,김선호 제어로봇시스템학회 2020 제어로봇시스템학회 국내학술대회 논문집 Vol.2020 No.7

Clinical Application of Artificial Intelligence-Based Computed Tomography Analysis of Myosteatosis in Localized Renal Cell Carcinoma

강병진,김경환,홍승백,이남경,김석,김시환,하홍구 대한비뇨기종양학회 2024 Journal of Urologic Oncology Vol.22 No.3

Purpose: Myosteatosis, defined as fat infiltration in muscle tissue, has been linked to poor outcomes in various cancers. However, the prognostic impact of myosteatosis on renal cell carcinoma (RCC) remains poorly understood. This study evaluated the predictive value of myosteatosis based on an artificial intelligence (AI)-driven computed tomography (CT) analysis in patients with localized RCC who underwent partial nephrectomy. Materials and Methods: This retrospective study included 170 patients with localized RCC who underwent partial nephrectomy at a single institution between 2011 and 2017. Myosteatosis was assessed on CT scans using an AI-based tool. The patients were categorized into 2 groups according to the presence or absence of myosteatosis. The clinical outcomes, including disease-free survival (DFS), were compared to determine the prognostic significance of myosteatosis. Results: Of 170 patients, 36 (21.2%) were diagnosed with myosteatosis. These patients were older and had a higher body mass index. The myosteatosis group had a higher proportion of females than the no myosteatosis group. Lymphovascular invasion and tumor necrosis were prevalent pathological features in patients with myosteatosis. Kaplan-Meier analysis demonstrated that myosteatosis was associated with significantly shorter DFS (p<0.05). Multivariate analysis confirmed that myosteatosis independently predicted adverse outcomes in patients with localized RCC. Conclusion: AI-based CT analysis of myosteatosis is a reliable method for improving the risk stratification of patients with localized RCC. Patients with myosteatosis demonstrate poor pathological features and shorter DFS. These findings highlight the potential of AI-driven body composition analysis to refine prognostic models and personalized treatment strategies.