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Intracranial pressure (ICP) refers to the pressure within the skull and is known to have significant importance in revealing the compliance state of the brain. Due to the invasive nature of the ICP measurement, many researches have attempted noninvasive approaches of colletcing ICP information with limited clinical applications. In this paper, a wavelet based K-means clustering analysis has been conducted...
Traumatic brain injury (TBI) and its complications, including intracranial hypertension, are one of the leading causes of mortality. Many proposed algorithms have attempted to overcome the invasiveness of intracranial pressure monitoring with limited clinical applications. In medical practices, changes of intracranial hypertension are perceived manually, by clinical experts, via surgical placement...
A large volume of data is steadily produced by the healthcare industry on daily basis. Data mining and machine learning approaches are two effective techniques applicable for data analysis and finding the hidden patterns which can be utilized for medical decision making. As the decisions in medical field are dealing with patient outcome, a high level of accuracy in data mining is needed. In this paper...
Generally wireless sensor networks rely of many-to-one communication approach for data gathering. This approach is extremely susceptible to sinkhole attack, where an intruder attracts surrounding nodes with unfaithful routing information, and subsequently presents selective forwarding or change the data that carry through it. A sinkhole attack causes an important threat to sensor networks and it should...
Wireless Sensor Networks (WSNs) are employed in numerous applications in different areas including military, ecology, and health; for example, to control of important information like the personnel position in a building, as a result, WSNs need security. However, several restrictions such as low capability of computation, small memory, limited resources of energy, and the unreliable channels employ...
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