Interpretable and Robust AI in EEG Systems: A Survey

The close coupling of artificial intelligence (AI) and electroencephalography (EEG) has substantially advanced human-computer interaction (HCI) technologies in the AI era. Different from traditional EEG systems, the interpretability and robustness of AI-based EEG systems are becoming particularly crucial. The interpretability clarifies the inner working mechanisms of AI models and thus can gain the trust of users. The robustness reflects the AI's reliability against attacks and perturbations, which is essential for sensitive and fragile EEG signals. Thus the interpretability and robustness of AI in EEG systems have attracted increasing attention, and their research has achieved great progress recently. However, there is still no survey covering recent advances in this field. In this paper, we present the first comprehensive survey and summarize the interpretable and robust AI techniques for EEG systems. Specifically, we first propose a taxonomy of interpretability by characterizing it into three types: backpropagation, perturbation, and inherently interpretable methods. Then we classify the robustness mechanisms into four classes: noise and artifacts, human variability, data acquisition instability, and adversarial attacks. Finally, we identify several critical and unresolved challenges for interpretable and robust AI in EEG systems and further discuss their future directions

Consumption coagulopathy in acute aortic dissection: principles of management

Abstract Background The effect of acute aortic dissection itself on coagulopathy or surgery-related coagulopathy has never been specifically studied. The aim of the present study was to perioperatively describe consumption coagulopathy in patients with acute aortic dissection. Methods Sixty-six patients with acute type A aortic dissection were enrolled in this study from January 2015 to September 2016. Thirty-six patients with thoracic aortic aneurysms were used as a control group during the same period. Consumption coagulopathy was evaluated using standard laboratory tests, enzyme-linked immunosorbent assay and thromboelastograghy at five perioperative time-points. Results A significant reduction in clotting factors and fibrinogen was observed at the onset of acute aortic dissection. Enzyme-linked immunosorbent assay and thromboelastograghy also revealed a persistent systemic activation of the coagulation system and the consumption of clotting factors. In contrast, although platelet counts were consistently low, we did not find that platelet function was more impaired in the acute aortic dissection group than the control group. Conclusions After surgery, clotting factors and fibrinogen were more impaired than platelet function. Thus, we proposed that hemostatic therapy should focus on the rapid and sufficient supplementation of clotting factors and fibrinogen to improve consumption coagulopathy in patients with acute aortic dissection

Increased risk for the development of postoperative severe hypoxemia in obese women with acute type a aortic dissection

Abstract Background The purpose of this study is to identify the risk factors for postoperative severe hypoxemia after surgery for acute type A aortic dissection. Methods This was a single-center retrospective study including 112 consecutive patients undergoing urgent aortic arch surgery for acute type A aortic dissection between December 2016 and April 2017 at Beijing Anzhen Hospital. Results Multivariate logistic regression analysis identified female (OR, 12.978; 95% CI, 3.332 to 50.546; p < 0.001) and increased body mass index (OR, 1.473; 95% CI, 1.213 to 1.789; p < 0.001) as independent predictors of postoperative severe hypoxemia in patients with acute type A aortic dissection. Conclusions Obesity and female were independent risk factors for postoperative severe hypoxemia in patients with acute type A aortic dissection. More attention should be paid to preventing postoperative severe hypoxemia in obese women with acute type A aortic dissection

Deep Hypothermic Circulatory Arrest Does Not Show Better Protection for Vital Organs Compared with Moderate Hypothermic Circulatory Arrest in Pig Model

Background. Continued debates exist regarding the optimal temperature during hypothermic circulatory arrest in aortic arch repair for patients with type A aortic dissection. This study seeks to examine whether the use of moderate hypothermic circulatory arrest in a pig model provides comparable vital organ protection outcomes to the use of deep hypothermic circulatory arrest. Methods. Thirteen pigs were randomly assigned to 30 minutes of hypothermic circulatory arrest without cerebral perfusion at 15°C (n = 5), 25°C (n = 5), and a control group (n = 3). The changes in standard laboratory tests and capacity for protection against apoptosis in different vital organs were monitored with different temperatures of hypothermic circulatory arrest management in pig model to determine which temperature was optimal for hypothermic circulatory arrest. Results. There were no significant differences in the capacity for protection against apoptosis in vital organs between 2 groups (p > 0.05, respectively). Compared with the moderate hypothermic circulatory arrest group, the deep hypothermic circulatory arrest group had no significant advantages in terms of the biologic parameters of any other organs (p > 0.05). Conclusions. Compared with deep hypothermic circulatory arrest, moderate hypothermic circulatory arrest is a moderate technique that has similar advantages with regard to the levels of biomarkers of injury and capacity for protection against apoptosis in vital organs

Claim Amount Forecasting and Pricing of Automobile Insurance Based on the BP Neural Network

The BP neural network model is a hot issue in recent academic research, and it has been successfully applied to many other fields, but few researchers apply the BP neural network model to the field of automobile insurance. The main method that has been used in the prediction of the total claim amount in automobile insurance is the generalized linear model, where the BP neural network model could provide a different approach to estimate the total claim loss. This paper uses a genetic algorithm to optimize the structure of the BP neural network at first, and the calculation speed is significantly improved. At the same time, by considering the overfitting problem, an early stop method is introduced to avoid the overfitting problem. In the model, a three-layer BP neural network model, which includes the input layer, hidden layer, and output layer, is trained. With consideration of various factors, a total claim amount prediction model is established, and the trained BP neural network model is used to predict the total claim amount of automobile insurance based on the data of the training set. The results show that the accuracy of the prediction by using the BP neural network model to both the data of Shandong Province and to the data of six cities is over 95%. Then, the predicted total claim amount is used to calculate premiums for five cities in Shandong Province according to credibility theory. The results show that the average premium of the five cities is slightly higher than the actual claim amount of the city. The combination of BP neural network and credibility theory can perform accurate claim amount estimation and pricing for automobile insurance, which can effectively improve the current situation of the automobile insurance business and promote the development of insurance industry

Experimental Evaluation of the Blackbody Radiation Shift in the Cesium Atomic Fountain Clock

The cesium atomic fountain clock is the world&rsquo;s most accurate microwave atomic clock. The uncertainty of blackbody radiation (BBR) shift accounts for an increasingly large percentage of the uncertainty associated with fountain clocks and has become a key factor in the performance of fountain clocks. The uncertainty of BBR shift can be reduced by improving the system environment temperature. This study examined the mechanism by which the BBR shift of the transition frequency between the two hyperfine energy levels of the 133Cs ground state is generated and the calculation method for the BBR shift in the atomic fountain. Methods used to reduce the uncertainty of BBR shift were also examined. A fountain system structure with uniform temperature and good heat preservation was designed, and related technologies, such as that for measuring the temperature of the cesium fountain system, were studied. The results of 20 days of measurements, in combination with computer simulation results, showed that the temperature uncertainty of the atomic action zone is 0.12 &deg;C and that the resulting uncertainty of BBR shift is 2.4 &times; 10&minus;17

Experimental Evaluation of the Blackbody Radiation Shift in the Cesium Atomic Fountain Clock

The cesium atomic fountain clock is the world’s most accurate microwave atomic clock. The uncertainty of blackbody radiation (BBR) shift accounts for an increasingly large percentage of the uncertainty associated with fountain clocks and has become a key factor in the performance of fountain clocks. The uncertainty of BBR shift can be reduced by improving the system environment temperature. This study examined the mechanism by which the BBR shift of the transition frequency between the two hyperfine energy levels of the 133Cs ground state is generated and the calculation method for the BBR shift in the atomic fountain. Methods used to reduce the uncertainty of BBR shift were also examined. A fountain system structure with uniform temperature and good heat preservation was designed, and related technologies, such as that for measuring the temperature of the cesium fountain system, were studied. The results of 20 days of measurements, in combination with computer simulation results, showed that the temperature uncertainty of the atomic action zone is 0.12 °C and that the resulting uncertainty of BBR shift is 2.4 × 10−17

Cardiopulmonary bypass time is an independent risk factor for acute kidney injury in emergent thoracic aortic surgery: a retrospective cohort study

Abstract Background Thoracic aortic surgery and cardiopulmonary bypass are both associated with development of postoperative acute kidney injury. In this study, we undertook to investigate the relationship between cardiopulmonary bypass time and postoperative acute kidney injury in patients undergoing thoracic aortic surgery for acute DeBakey Type I aortic dissection. Methods All patients receiving thoracic aortic surgery for acute DeBakey Type I aortic dissection in Beijing Anzhen hospital from December 2015 to April 2017 were included. Cardiopulmonary bypass time was recorded during surgery. Acute kidney injury was defined based on the Kidney Disease Improving Global Outcomes criteria. A total of 115 consecutive patients were eventually analyzed. Results The overall incidence of acute kidney injury was 53.0% (n = 61). The average age was 47.8 ± 10.7 years; 74.8% were male. Mean cardiopulmonary bypass time was 211 ± 56 min. In-hospital mortality was 7.8%. Multivariate logistic regression revealed that cardiopulmonary bypass time was independently associated with the occurrence of postoperative acute kidney injury after adjust confounding factors (odds ratio = 1.171; 95% confidence interval: 1.002–1.368; P = 0.047). Conclusions Cardiopulmonary bypass time is independently associated with an increased hazard of acute kidney injury after thoracic aortic surgery for acute DeBakey Type I aortic dissection. Further understanding of the mechanism of this association is crucial to the design of preventative strategies