• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.4
• /
• pp.1080-1099
• /
• 2023

Digital healthcare combined with telemedicine services in the form of convergence with digital technology and AI is developing rapidly. Digital healthcare research is being conducted on many conditions including shock. However, the causes of shock are diverse, and the treatment is very complicated, requiring a high level of medical knowledge. In this paper, we propose a shock detection method based on the correlation between shock and data extracted from hemodynamic monitoring equipment. From the various parameters expressed by this equipment, four parameters closely related to patient shock were used as the input data for a machine learning model in order to detect the shock. Using the four parameters as input data, that is, feature values, a random forest-based ensemble machine learning model was constructed. The value of the mean arterial pressure was used as the correct answer value, the so called label value, to detect the patient's shock state. The performance was then compared with the decision tree and logistic regression model using a confusion matrix. The average accuracy of the random forest model was 92.80%, which shows superior performance compared to other models. We look forward to our work playing a role in helping medical staff by making recommendations for the diagnosis and treatment of complex and difficult cases of shock.

• Journal of the Korean Data and Information Science Society
• /
• v.15 no.4
• /
• pp.773-782
• /
• 2004

In this paper, a random shock model for a system is considered. Each shock arriving according to a Poisson process decreases the state of the system by a random amount. A repairman arriving according to another Poisson process of rate $\lambda$ repairs the system only if the state of the system is below a threshold $\alpha$. After assigning various costs to the system, we calculate the long-run average cost and show that there exist a unique value of arrival rate $\lambda$ and a unique value of threshold $\alpha$ which minimize the long-run average cost per unit time.

• 한국데이터정보과학회:학술대회논문집
• /
• 2004.10a
• /
• pp.33-42
• /
• 2004

In this paper, a random shock model for a system is considered. Each shock arriving according to a Poisson process decreases the state of the system by a random amount. A repairman arriving according to another Poisson process of rate $\lambda$ repairs the system only if the state of the system is below a threshold $\alpha$. After assigning various costs to the system, we calculate the long-run average cost and show that there exist a unique value of arrival rate $\lambda$ and a unique value of threshold $\alpha$ which minimize the long-run average cost per unit time.

• Journal of the Korean Statistical Society
• /
• v.24 no.2
• /
• pp.471-479
• /
• 1995

A random shock model for a linearly deteriorating system is introduced. The system deteriorating linearly with time is subject to random shocks which arrive according to a Poisson process and decrease the state of the system by a random amount. The system is repaired by a repairmen arriving according to another Poisson process if the state when he arrives is below a threshold. Explicit expressions are deduced for the characteristic function of the distribution function of X(t), the state of the system at time t, and for the distribution function of X(t) if X(t) is over the threshold. The stationary case is briefly discussed.

• Journal of the Korean Data and Information Science Society
• /
• v.16 no.4
• /
• pp.725-733
• /
• 2005

A system subject to random shocks is considered. The shocks arrive according to a Poisson process and the amount of each shock is exponentially distributed. In this paper, a periodic inspection policy for the system is compared with a random inspection policy. After assigning several maintenance costs to the system, we calculate and compare the long-run average costs per unit time under two policies.

• Journal of Biomedical Engineering Research
• /
• v.33 no.3
• /
• pp.148-154
• /
• 2012

Hemorrhagic shock is a primary cause of deaths resulting from injury in the world. Although many studies have tried to diagnose accurately hemorrhagic shock in the early stage, such attempts were not successful due to compensatory mechanisms of humans. The objective of this study was to construct a survival prediction model of rats in acute hemorrhagic shock using a random forest (RF) model. Heart rate (HR), mean arterial pressure (MAP), respiration rate (RR), lactate concentration (LC), and peripheral perfusion (PP) measured in rats were used as input variables for the RF model and its performance was compared with that of a logistic regression (LR) model. Before constructing the models, we performed 5-fold cross validation for RF variable selection, and forward stepwise variable selection for the LR model to examine which variables were important for the models. For the LR model, sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (ROC-AUC) were 0.83, 0.95, 0.88, and 0.96, respectively. For the RF models, sensitivity, specificity, accuracy, and AUC were 0.97, 0.95, 0.96, and 0.99, respectively. In conclusion, the RF model was superior to the LR model for survival prediction in the rat model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2011.04a
• /
• pp.538-543
• /
• 2011

In this paper, optimal spot weld layout design of the shock tower structure is performed for increasing fatigue life of spot weld and fatigue life of shock tower simultaneously. To predict the fatigue life, linear static analysis is conducted then fatigue analysis is performed by applying random vibration load. To optimize the spot weld layout, design variables that have an effect on spot weld fatigue life are selected. Based on the DOE table, spot weld fatigue analysis is conducted. Finally, response surface model is made from fatigue analysis results and optimized spot weld layout model which increases fatigue life of sport weld and fatigue life of shock tower is determined.

• Journal of Korean Society for Quality Management
• /
• v.24 no.3
• /
• pp.31-36
• /
• 1996

A Markovian stochastic model for a system subject to random shocks is considered. Each shock arriving according to a Poisson process decreases the state of the system by a random amount. A repairman arrives at the system periodically for inspection and repairs the system only if the state is below a threshold. Costs are assigned to each inspection of the repairman, to each repair, and to the system being in bad states below the threshold. The expected long run average cost is obtained and compared with that of the random inspection introduced by Lee and Lee(1994).

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.21 no.9
• /
• pp.798-804
• /
• 2011

In this paper, optimal spot weld layout design for a shock tower structure is presented. This design increases the fatigue life of the spot-welds thereby increasing the fatigue life of the shock tower itself. In order to predict the fatigue life, a quasi-static analysis has been conducted then a fatigue analysis was performed through the application of random vibration loads. In order to optimize the spot weld layout, the design variables that have an effect on the spot weld fatigue life were determined. A spot weld fatigue analysis was then conducted based on the experiment design. Finally, a response surface model was made using the fatigue analysis results and an optimized spot weld layout model, one that increases the fatigue life of the spot welds and thereby the fatigue life of the shock tower, was developed.

• Journal of the military operations research society of Korea
• /
• v.10 no.1
• /
• pp.23-39
• /
• 1984

Consider a failure model for a stochastic system. A shock is any perturbation to the system which causes a random amount of damage to the system. Any of the shocks can cause the system to fail at shock times. The amount of damage at each shock is a function of the sum of the magnitudes of damage caused from all previous shocks. The times between shocks form a sequence of independent and identically distributed random variables. The system must be replaced upon failure at some cost but it also can be replaced before failure at a lower cost. The long term expected cost per unit time criterion is used. Structural relationships of the optimal replacement policy under the appropriate regularity conditions will be developed. And these relationships will provide theoretical background for the algorithm development.