Classification of Radiology Reports Using Neural Attention Models

The electronic health record (EHR) contains a large amount of multi-dimensional and unstructured clinical data of significant operational and research value. Distinguished from previous studies, our approach embraces a double-annotated dataset and strays away from obscure "black-box" models to comprehensive deep learning models. In this paper, we present a novel neural attention mechanism that not only classifies clinically important findings. Specifically, convolutional neural networks (CNN) with attention analysis are used to classify radiology head computed tomography reports based on five categories that radiologists would account for in assessing acute and communicable findings in daily practice. The experiments show that our CNN attention models outperform non-neural models, especially when trained on a larger dataset. Our attention analysis demonstrates the intuition behind the classifier's decision by generating a heatmap that highlights attended terms used by the CNN model; this is valuable when potential downstream medical decisions are to be performed by human experts or the classifier information is to be used in cohort construction such as for epidemiological studies

Robust face anti-spoofing framework with Convolutional Vision Transformer

Owing to the advances in image processing technology and large-scale datasets, companies have implemented facial authentication processes, thereby stimulating increased focus on face anti-spoofing (FAS) against realistic presentation attacks. Recently, various attempts have been made to improve face recognition performance using both global and local learning on face images; however, to the best of our knowledge, this is the first study to investigate whether the robustness of FAS against domain shifts is improved by considering global information and local cues in face images captured using self-attention and convolutional layers. This study proposes a convolutional vision transformer-based framework that achieves robust performance for various unseen domain data. Our model resulted in 7.3%$p$ and 12.9%$p$ increases in FAS performance compared to models using only a convolutional neural network or vision transformer, respectively. It also shows the highest average rank in sub-protocols of cross-dataset setting over the other nine benchmark models for domain generalization.Comment: ICIP 202

Value Discount of Business Groups Surrounding the Asia Financial Crisis: Evidence from Korean Chaebols

Asian Financial Crisis, Business Group, Chaebol, Diversification, Firm Value

The roles of sodium and volume overload on hypertension in chronic kidney disease

Chronic kidney disease (CKD) is associated with increased risk of cardiovascular (CV) events, and the disease burden is rising rapidly. An important contributor to CV events and CKD progression is high blood pressure (BP). The main mechanisms of hypertension in early and advanced CKD are renin-angiotensin system activation and volume overload, respectively. Sodium retention is well known as a factor for high BP in CKD. However, a BP increase in response to total body sodium or volume overload can be limited by neurohormonal modulation. Recent clinical trial data favoring intensive BP lowering in CKD imply that the balance between volume and neurohormonal control could be revisited with respect to the safety and efficacy of strict volume control when using antihypertensive medications. In hemodialysis patients, the role of more liberal use of antihypertensive medications with the concept of functional dry weight for intensive BP control must be studied

A case report of type VI dual left anterior descending coronary artery anomaly presenting with non-ST-segment elevation myocardial infarction

BACKGROUND: Type VI dual left anterior descending artery (LAD) is a rare coronary anomaly, the first case of which has recently been described. This is the first report of type VI dual LAD anomaly in which the patient presented with non-ST-segment elevation myocardial infarction and percutaneous coronary intervention was performed in the anomalously originating LAD. CASE PRESENTATION: A 52-year-old man with diabetes, hypertension and hyperlipidemia presented with chest pain without ST elevation on EKG, although the patient’s troponin I level was elevated. Coronary angiography revealed a short LAD originating from the left main coronary artery and a long LAD originating from the proximal portion of the right coronary artery (RCA). Three-dimensional reconstruction of computed tomography of images revealed that the long LAD originated from the proximal RCA and coursed between the right ventricular outflow tract (RVOT) and the aortic root before entering the mid anterior interventricular groove. The high take-off RCA originated underneath the RVOT, pointing downwards and forming an acute angle with the proximal portion of the long LAD. The anomalous long LAD displayed significant stenosis. We performed successful percutaneous coronary intervention (PCI) in the anomalous artery. CONCLUSION: With accurate understanding of the coronary anatomy and appropriate hardware selection, successful PCI can be performed in the in the long LAD in patients with type VI dual LAD anomaly

The impact of UK household overconfidence in public information on house prices

We investigate if house prices are affected by overconfidence of households who predict house prices using imperfect public information about economic outlook. For this purpose, we develop a new measure of household overconfidence in the Bayesian framework. For the three variables we test – changes in consumption, stock returns, and changes in human capital, we find that UK households were overconfident about the signals of consumption regardless of regions. However, households in London were overconfident about the signals of stock markets whereas those remote from London were overconfident about the signals of human capital. The results of household overconfidence appear positive in the UK housing market for our sample period from 1980 to 2018, in particular, 0.5% per quarter in London