이현훈 교수

Predicting in-hospital cardiac arrest in patients admitted to an intensive care unit (ICU) allows prompt interventions to improve patient outcomes. We developed and validated a machine learning-based real-time model for in-hospital cardiac arrest predictions using electrocardiogram (ECG)-based heart rate variability (HRV) measures. The HRV measures, including time/frequency domains and nonlinear measures, were calculated from 5 min epochs of ECG signals from ICU patients. A light gradient boosti

With the increasing need for telemedicine during the current COVID-19 pandemic, an AI chatbot with a deep learning-based NLP model that can recommend a medical specialty to patients through their smartphones would be exceedingly useful. This chatbot allows patients to identify the proper medical specialist in a rapid and contactless manner, based on their symptoms, thus potentially supporting both patients and primary care providers.

Abstract The central objective of this paper is to empirically evaluate the degree of linkages among East Asian equity and bond markets. Using data from the IMF’s Coordinated Portfolio Investment Survey (CPIS), we find that intra‐East Asian financial asset holdings of four East Asian countries – Japan, Korea, Hong Kong and Singapore – are larger than the levels predicted by the financial gravity model. However, our analysis suggests that this result is likely to be driven by intra‐regional trade

In recent years China, Japan and Korea, the three major economies in East Asia, have been gearing up their efforts to sign free trade agreements with many different regions and countries. One of the main reasons for this is that they fear that with a regionalism movement rising in every corner of the world, their exports are discriminated against and diverted in the trading blocs of other nations. The main purpose of this paper is to investigate whether this is a real fear. We utilise the gravit

Abstract Since the World Trade Organization ( WTO ) Doha Development Agenda ( DDA ) negotiations started in 2001, the importance of aid for trade (AfT) has been well recognised as a useful tool for facilitating trade, economic growth and social development in developing countries. At the WTO Hong Kong Ministerial Conference in December 2005, the ‘AfT initiative’ was launched and many high‐income member countries pledged to increase their AfT contributions, particularly for the least developed me

Abstract Many studies have found that Aid for Trade (AfT) is effective in promoting the exports and imports of recipient countries. Recently, Gnangnon ( The World Economy , 42, 2019 and 396) and Kim ( The World Economy , 42, 2019 and 2684) found that AfT also contributes to the export diversification of recipient countries. We extend previous studies by assessing the effects of AfT on import diversification of recipient countries by estimating a two‐step System GMM on a data set of 104 countries

These results indicate that Stemona tuberosa has significant effects on lung inflammation in a subacute CS-induced mouse model. According to these outcomes, Stemona tuberosa may represent a novel therapeutic herb for the treatment of lung diseases including COPD.

ChatGPT may be a useful educational tool for acupuncture students, providing valuable insights into personalized treatment plans. However, it cannot fully replace traditional diagnostic methods, and further studies are needed to ensure its safe and effective implementation in acupuncture education.

Ventilation should be assisted without asynchrony or cardiorespiratory instability during anesthesia emergence until sufficient spontaneous ventilation is recovered. In this multicenter cohort study, we develop and validate a reinforcement learning-based Artificial Intelligence model for Ventilation control during Emergence (AIVE) from general anesthesia. Ventilatory and hemodynamic parameters from 14,306 surgical cases at an academic hospital between 2016 and 2019 are used for training and inte

Pattern identification (PI) is a diagnostic method used in Traditional East Asian medicine (TEAM) to select appropriate and personalized acupuncture points and herbal medicines for individual patients. Developing a reproducible PI model using clinical information is important as it would reflect the actual clinical setting and improve the effectiveness of TEAM treatment. In this paper, we suggest a novel deep learning-based PI model with feature extraction using a deep autoencoder and <i>k</i>-m