| Contents |
Introduction to physiological modeling in medicine : a survey of existing methods, approaches, and trends. Overview ; The art of modeling and prediction ; Why model? ; Multivariate models and model complexity ; Clinical informatics and meaningful use ; Types of models ; Stochastic modeling and Monte Carlo simulation ; Guidelines and protocols ; Summary -- Simulation and modeling techniques. simulating physical systems ; Introduction to Monte Carlo simulation ; Introduction to discrete event simulation models ; Deterministic mathematical models ; Probability and statistics ; Sensitivity, specifity and confidence intervals ; Chi-square tests ; The concept of x2 and the assignment problem ; Other applications of optimal assignment methodologies ; Noise and error representation ; Queuing theory deep dive and examples ; Summary -- Introduction to automatic control systems theory and applications. State space modeling ; Controllability and observability ; The feedback control loop ; System stability ; Techniques for representing physical phenomena -- Physical system modeling and state representation. Fluid mechanics applications ; Electrical signal and circuit analogs to physical systems ; Simplified physiological systems modeling -- Medical device data measurement, interoperability, interfacing, and analysis. Types of medical devices used for physiological measurement ; Medical device interfaces, standards, and interoperability initiatives ; Medical device data collection, validation, and clinical use ; Biomedical device interoperability and the electronic medical record ; Associating biomedical device data with patients ; Spatial-temporal modeling of medical device data ; Biomedical data storage and retrieval ; Applying wavelet transforms to biomedical device data ; Summary -- Systems modeling example applications. Modeling to assist diagnosis and treatment ; Clinical workflow and decision support ; Systems modeling and integration ; Integrating clinical decision support systems within clinical information systems ; Summary -- Modeling benefits, cautions, and future work -- Appendix. Monte Carlo simulation : computing [pi] ; Monte Carlo simulation : stereo viewing covariance model ; Optimal assignment algorithm ; Simple discrete event model ; Gaussian random number generation ; Poisson and exponentially distributed random numbers ; Java applet plotter ; Kalman filter ; Line plotter ; Control systems modeling : spring mass response to step function. |
