Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Acute kidney injury (AKI) is a complex disorder for which currently there is no accepted definition. Having a uniform standard for diagnosing and classifying AKI would enhance our ability to manage these patients. Future clinical and translational research in AKI will require collaborative networks of investigators drawn from various disciplines, dissemination of information via multidisciplinary joint conferences and publications, and improved translation of knowledge from pre-clinical research. We describe an initiative to develop uniform standards for defining and classifying AKI and to establish a forum for multidisciplinary interaction to improve care for patients with or at risk for AKI. Members representing key societies in critical care and nephrology along with additional experts in adult and pediatric AKI participated in a two day conference in Amsterdam, The Netherlands, in September 2005 and were assigned to one of three workgroups. Each group's discussions formed the basis for draft recommendations that were later refined and improved during discussion with the larger group. Dissenting opinions were also noted. The final draft recommendations were circulated to all participants and subsequently agreed upon as the consensus recommendations for this report. Participating societies endorsed the recommendations and agreed to help disseminate the results. The term AKI is proposed to represent the entire spectrum of acute renal failure. Diagnostic criteria for AKI are proposed based on acute alterations in serum creatinine or urine output. A staging system for AKI which reflects quantitative changes in serum creatinine and urine output has been developed. We describe the formation of a multidisciplinary collaborative network focused on AKI. We have proposed uniform standards for diagnosing and classifying AKI which will need to be validated in future studies. The Acute Kidney Injury Network offers a mechanism for proceeding with efforts to improve patient outcomes.

Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury

An analyte monitor includes a sensor, a sensor control unit, and a display unit. The sensor has, for example, a substrate, a recessed channel formed in the substrate, and conductive material disposed in the recessed channel to form a working electrode. The sensor control unit typically has a housing adapted for placement on skin and is adapted to receive a portion of an electrochemical sensor. The sensor control unit also includes two or more conductive contacts disposed on the housing and configured for coupling to two or more contact pads on the sensor. A transmitter is disposed in the housing and coupled to the plurality of conductive contacts for transmitting data obtained using the sensor. The display unit has a receiver for receiving data transmitted by the transmitter of the sensor control unit and a display coupled to the receiver for displaying an indication of a level of an analyte. The analyte monitor may also be part of a drug delivery system to alter the level of the analyte based on the data obtained using the sensor.

Analyte Monitoring Device And Methods Of Use

An infusion system for infusing a liquid into a body includes an external infusion device and a remote commander. The external infusion device includes a housing, a receiver, a processor and an indication device. The receiver is coupled to the housing and for receiving remotely generated commands. The processor is coupled to the housing and the receiver to receive remotely generated commands and to control the external infusion device in accordance with the commands. The indication device indicates when a command has been received and indicates when the command is being utilized to control the external infusion device so that the external infusion device is capable of being concealed from view when being remotely commanded. The remote commander includes a commander housing, a keypad for transmitting commands, and a transmitter for transmitting commands to the receiver of the external infusion device.

External infusion device with remote programming, bolus estimator and/or vibration alarm capabilities

Carbon nanotubes exhibit many unique intrinsic physical and chemical properties and have been intensively explored for biological and biomedical applications in the past few years. In this comprehensive review, we summarize the main results from our and other groups in this field and clarify that surface functionalization is critical to the behavior of carbon nanotubes in biological systems. Ultrasensitive detection of biological species with carbon nanotubes can be realized after surface passivation to inhibit the non-specific binding of biomolecules on the hydrophobic nanotube surface. Electrical nanosensors based on nanotubes provide a label-free approach to biological detection. Surface-enhanced Raman spectroscopy of carbon nanotubes opens up a method of protein microarray with detection sensitivity down to 1 fmol/L. In vitro and in vivo toxicity studies reveal that highly water soluble and serum stable nanotubes are biocompatible, nontoxic, and potentially useful for biomedical applications. In vivo biodistributions vary with the functionalization and possibly also size of nanotubes, with a tendency to accumulate in the reticuloendothelial system (RES), including the liver and spleen, after intravenous administration. If well functionalized, nanotubes may be excreted mainly through the biliary pathway in feces. Carbon nanotube-based drug delivery has shown promise in various In vitro and in vivo experiments including delivery of small interfering RNA (siRNA), paclitaxel and doxorubicin. Moreover, single-walled carbon nanotubes with various interesting intrinsic optical properties have been used as novel photoluminescence, Raman, and photoacoustic contrast agents for imaging of cells and animals. Further multidisciplinary explorations in this field may bring new opportunities in the realm of biomedicine.

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Carbon Nanotubes in Biology and Medicine: In vitro and in vivo Detection, Imaging and Drug Delivery

A model-based-predictive control algorithm is developed to maintain normoglycemia in the Type I diabetic patient using a closed-loop insulin infusion pump. Utilizing compartmental modeling techniques, a fundamental model of the diabetic patient is constructed. The resulting nineteenth-order nonlinear pharmacokinetic-pharmacodynamic representation is used in controller synthesis. Linear identification of an input-output model from noisy patient data is performed by filtering the impulse-response coefficients via projection onto the Laguerre basis. A linear model predictive controller is developed using the identified step response model. Controller performance for unmeasured disturbance rejection (50 g oral glucose tolerance test) is examined. Glucose setpoint tracking performance is improved by designing a second controller which substitutes a more detailed internal model including state-estimation and a Kalman filter for the input-output representation The state-estimating controller maintains glucose within 15 mg/dl of the setpoint in the presence of measurement noise. Under noise-free conditions, the model based predictive controller using state estimation outperforms an internal model controller from literature (49.4% reduction in undershoot and 45.7% reduction in settling time). These results demonstrate the potential use of predictive algorithms for blood glucose control in an insulin infusion pump.

A model-based algorithm for blood glucose control in Type I diabetic patients

A robust H∞ controller was developed to deliver insulin via a mechanical pump in Type I diabetic patients. A fundamental nonlinear diabetic patient model was linearized and then reduced to a third-order linear form for controller synthesis. Uncertainty in the nonlinear model was characterized by up to ± 40% variation in eight physiological parameters. A sensitivity analysis identified the three-parameter set having the most significant effect on glucose and insulin dynamics over the frequency range of interest ω = [0.002, 0.2] (rad/min). This uncertainty was represented in the frequency domain and incorporated in the controller design. Controller performance was assessed in terms of its ability to track a normoglycemic set point (81.1 mg/dL) in response to a 50 g meal disturbance. In the nominal continuous-time case, the controller maintained glucose concentrations within ± 3.3 mg/dL of set point. A controller tuned to accommodate uncertainty yielded a maximum deviation of 17.6 mg/dL for the worst-case parameter variation.

/pdf/robust-h-glucose-control-in-diabetes-using-a-physiological-51hrpcfpt5.pdf

Robust H∞ glucose control in diabetes using a physiological model

This article discusses closed-loop blood glucose regulation algorithms that use the intravenous route for insulin delivery to insulin-dependent diabetic patients. Classical control methods and advanced algorithms using implicit knowledge or explicit models (empirical, fundamental, or "gray-box") of the diabetic patient are examined. Current research on characterizing patient variability is presented, in the context of a model predictive controller able to adjust to changes in patient glucose and insulin sensitivity.

The intravenous route to blood glucose control

In this work, several aspects of in vivo glucose detection using a nanotube-based optical sensor are considered. The optical properties of commonly used organic and nanoparticle fluorescent probes are compared with respect to quantum yield, human tissue penetration, and photobleaching stability. The latter two factors are shown to dominate sensor viability and require a near-infrared nanoparticle fluorophore for practical device operation. The dynamics of a model optical sensor are compared to a flux-measuring electrochemical sensor of equal area using a mathematical simulation of a healthy patient ingesting three predefined meals per day. Both sensors demonstrate an approximately linear response to blood glucose levels. It is shown that the optical sensor, which transduces glucose concentration, not flux, directly is significantly more stable to membrane biofouling.

In vivo fluorescence detection of glucose using a single-walled carbon nanotube optical sensor: design, fluorophore properties, advantages, and disadvantages.

Robert S. Parker

Papers

A model-based algorithm for blood glucose control in Type I diabetic patients

Robust H∞ glucose control in diabetes using a physiological model

The intravenous route to blood glucose control

In vivo fluorescence detection of glucose using a single-walled carbon nanotube optical sensor: design, fluorophore properties, advantages, and disadvantages.

Control-relevant modeling in drug delivery.