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Real-time Outbreak And Disease Surveillance
Real-time outbreak and disease surveillance system (RODS) is a syndromic surveillance system developed by the University of Pittsburgh, Department of Biomedical Informatics. It is "prototype developed at the University of Pittsburgh where real-time clinical data from emergency departments within a geographic region can be integrated to provide an instantaneous picture of symptom patterns and early detection of epidemic events."''Public Health-Related Activities'' at thUS HHS government website Accessed December 2, 2010. RODS uses a combination of various monitoring tools. # The first tool is a moving average with a 120-day sliding phase-I-window. # The second tool is a nonstandard combination of CUSUM and EWMA, where an EWMA is used to predict next-day counts, and a CuSum monitors the residuals from these predictions. # The third monitoring tool in RODS is a recursive least squares (RLS) algorithm, which fits an autoregressive model to the counts and updates estimates continuous ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Syndromic Surveillance
Public health surveillance (also epidemiological surveillance, clinical surveillance or syndromic surveillance) is, according to the World Health Organization (WHO), "the continuous, systematic collection, analysis and interpretation of health-related data needed for the planning, implementation, and evaluation of public health practice."Public health surveillance (accessed January 14, 2016). Public health surveillance may be used to track emerging health-related issues at an early stage and find active solutions in a timely manner. Surveillance systems are generally called upon to provide information regarding when and where heal ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
University Of Pittsburgh
The University of Pittsburgh (Pitt) is a public state-related research university in Pittsburgh, Pennsylvania. The university is composed of 17 undergraduate and graduate schools and colleges at its urban Pittsburgh campus, home to the university's central administration and around 28,000 undergraduate and graduate students. The 132-acre Pittsburgh campus includes various historic buildings that are part of the Schenley Farms Historic District, most notably its 42-story Gothic revival centerpiece, the Cathedral of Learning. Pitt is a member of the Association of American Universities and is classified among "R1: Doctoral Universities – Very high research activity". It is the second-largest non-government employer in the Pittsburgh metropolitan area. Pitt traces its roots to the Pittsburgh Academy founded by Hugh Henry Brackenridge in 1787. While the city was still on the edge of the American frontier at the time, Pittsburgh's rapid growth meant that a proper university w ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Informatics (academic Field)
Informatics is the study of computational systems, especially those for data storage and retrieval. According to ACM ''Europe and'' '' Informatics Europe'', informatics is synonymous with computer science and computing as a profession, in which the central notion is transformation of information. In other countries, the term "informatics" is used with a different meaning in the context of library science. Different meanings In some countries, depending on local interpretations, the term "informatics" is used synonymously to mean information systems, information science, information theory, information engineering, information technology, information processing, or other theoretical or practical fields. In Germany, the term ''informatics'' almost exactly corresponds to modern computer science. Accordingly, universities in continental Europe usually translate "informatics" as computer science, or sometimes information and computer science, although technical universities may tr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Epidemic
An epidemic (from Greek ἐπί ''epi'' "upon or above" and δῆμος ''demos'' "people") is the rapid spread of disease to a large number of patients among a given population within an area in a short period of time. Epidemics of infectious diseases are generally caused by several factors including a significant change in the ecology of the areal population (e.g., increased stress maybe additional reason or increase in the density of a vector species), the introduction of an emerging pathogen to an areal population (by movement of pathogen or host) or an unexpected genetic change that is in the pathogen reservoir. Generally, epidemics concerns with the patterns of infectious disease spread. An epidemic may occur when host immunity to either an established pathogen or newly emerging novel pathogen is suddenly reduced below that found in the endemic equilibrium and the transmission threshold is exceeded. For example, in meningococcal infections, an attack rate in excess of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Moving Average
In statistics, a moving average (rolling average or running average) is a calculation to analyze data points by creating a series of averages of different subsets of the full data set. It is also called a moving mean (MM) or rolling mean and is a type of finite impulse response filter. Variations include: simple, cumulative, or weighted forms (described below). Given a series of numbers and a fixed subset size, the first element of the moving average is obtained by taking the average of the initial fixed subset of the number series. Then the subset is modified by "shifting forward"; that is, excluding the first number of the series and including the next value in the subset. A moving average is commonly used with time series data to smooth out short-term fluctuations and highlight longer-term trends or cycles. The threshold between short-term and long-term depends on the application, and the parameters of the moving average will be set accordingly. It is also used in economics ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
CUSUM
In statistical quality control, the CUsUM (or cumulative sum control chart) is a sequential analysis technique developed by E. S. Page of the University of Cambridge. It is typically used for monitoring change detection. CUSUM was announced in Biometrika, in 1954, a few years after the publication of Wald's sequential probability ratio test (SPRT). E. S. Page referred to a "quality number" \theta, by which he meant a parameter of the probability distribution; for example, the mean. He devised CUSUM as a method to determine changes in it, and proposed a criterion for deciding when to take corrective action. When the CUSUM method is applied to changes in mean, it can be used for step detection of a time series. A few years later, George Alfred Barnard developed a visualization method, the V-mask chart, to detect both increases and decreases in \theta. Method As its name implies, CUSUM involves the calculation of a cumulative sum (which is what makes it "sequential"). Samples fr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
EWMA
In statistics, a moving average (rolling average or running average) is a calculation to analyze data points by creating a series of averages of different subsets of the full data set. It is also called a moving mean (MM) or rolling mean and is a type of finite impulse response filter. Variations include: simple, cumulative, or weighted forms (described below). Given a series of numbers and a fixed subset size, the first element of the moving average is obtained by taking the average of the initial fixed subset of the number series. Then the subset is modified by "shifting forward"; that is, excluding the first number of the series and including the next value in the subset. A moving average is commonly used with time series data to smooth out short-term fluctuations and highlight longer-term trends or cycles. The threshold between short-term and long-term depends on the application, and the parameters of the moving average will be set accordingly. It is also used in economics ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recursive Least Squares
Recursive least squares (RLS) is an adaptive filter algorithm that recursively finds the coefficients that minimize a weighted linear least squares cost function relating to the input signals. This approach is in contrast to other algorithms such as the least mean squares (LMS) that aim to reduce the mean square error. In the derivation of the RLS, the input signals are considered deterministic, while for the LMS and similar algorithms they are considered stochastic. Compared to most of its competitors, the RLS exhibits extremely fast convergence. However, this benefit comes at the cost of high computational complexity. Motivation RLS was discovered by Gauss but lay unused or ignored until 1950 when Plackett rediscovered the original work of Gauss from 1821. In general, the RLS can be used to solve any problem that can be solved by adaptive filters. For example, suppose that a signal d(n) is transmitted over an echoey, noisy channel that causes it to be received as :x(n)=\sum_ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Autoregressive Model
In statistics, econometrics and signal processing, an autoregressive (AR) model is a representation of a type of random process; as such, it is used to describe certain time-varying processes in nature, economics, etc. The autoregressive model specifies that the output variable depends linearly on its own previous values and on a stochastic term (an imperfectly predictable term); thus the model is in the form of a stochastic difference equation (or recurrence relation which should not be confused with differential equation). Together with the moving-average (MA) model, it is a special case and key component of the more general autoregressive–moving-average (ARMA) and autoregressive integrated moving average (ARIMA) models of time series, which have a more complicated stochastic structure; it is also a special case of the vector autoregressive model (VAR), which consists of a system of more than one interlocking stochastic difference equation in more than one evolving random vari ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Prediction Error
In statistics the mean squared prediction error or mean squared error of the predictions of a smoothing or curve fitting procedure is the expected value of the squared difference between the fitted values implied by the predictive function \widehat and the values of the (unobservable) function ''g''. It is an inverse measure of the explanatory power of \widehat, and can be used in the process of cross-validation of an estimated model. If the smoothing or fitting procedure has projection matrix (i.e., hat matrix) ''L'', which maps the observed values vector y to predicted values vector \hat via \hat=Ly, then :\operatorname(L)=\operatorname\left left( g(x_i)-\widehat(x_i)\right)^2\right The MSPE can be decomposed into two terms: the mean of squared biases of the fitted values and the mean of variances of the fitted values: :n\cdot\operatorname(L)=\sum_^n\left(\operatorname\left widehat(x_i)\rightg(x_i)\right)^2+\sum_^n\operatorname\left widehat(x_i)\right Knowledge of ''g'' is ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Standard Deviations
In statistics, the standard deviation is a measure of the amount of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the values are spread out over a wider range. Standard deviation may be abbreviated SD, and is most commonly represented in mathematical texts and equations by the lower case Greek letter σ (sigma), for the population standard deviation, or the Latin letter '' s'', for the sample standard deviation. The standard deviation of a random variable, sample, statistical population, data set, or probability distribution is the square root of its variance. It is algebraically simpler, though in practice less robust, than the average absolute deviation. A useful property of the standard deviation is that, unlike the variance, it is expressed in the same unit as the data. The standard deviation of a po ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Wavelet
A wavelet is a wave-like oscillation with an amplitude that begins at zero, increases or decreases, and then returns to zero one or more times. Wavelets are termed a "brief oscillation". A taxonomy of wavelets has been established, based on the number and direction of its pulses. Wavelets are imbued with specific properties that make them useful for signal processing. For example, a wavelet could be created to have a frequency of Middle C and a short duration of roughly one tenth of a second. If this wavelet were to be convolved with a signal created from the recording of a melody, then the resulting signal would be useful for determining when the Middle C note appeared in the song. Mathematically, a wavelet correlates with a signal if a portion of the signal is similar. Correlation is at the core of many practical wavelet applications. As a mathematical tool, wavelets can be used to extract information from many different kinds of data, including but not limited to au ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
