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At least 865 records · Page 48Linked to original sources
PubMed1997

An age-adjusted trend test for the tumor incidence rate for multiple-sacrifice experiments.

The nonparametric age-adjusted trend test for the tumor incidence rate proposed by Malani and Lu (1993, Communications in Statistics--Theory and Methods 22, 1557-1584) is modified in two ways to improve the size of the test. First, the tumor incidence rate is constrained to be nonnegative, and second, a conditional variance is used in place of the asymptotic variance based on the delta method. A Monte Carlo simulation study demonstrates the improvement in size of test. The proposed test can be viewed also as a modification of the two-group test of Dewanji and Kalbfleisch (1986, Biometrics 42, 325-341), although their maximum likelihood routine is based on a different formulation of the problem.

Age Factors↗
PubMed1998

Duration and route of antibiotic therapy in community-acquired pneumonia: switch and step-down therapy.

The treatment of hospitalized patients with community-acquired pneumonia (CAP) has traditional been with intravenous antibiotics. More recently, the focus of this antibiotic therapy has been empiric and based on the most likely pathogens in a given patient. The concept of when and how to approach the patient for conversion to oral therapy, known as switch therapy, is now the focus of controversy. Recently, several studies have emerged from the literature that shed some light on the subject of switch therapy for CAP. Although the data are limited at this time, it seems clear that switching to oral antibiotics in selected low-risk patients may be feasible and safe. In this article, we focus on the problem and help formulate a practical approach to switching patients from intravenous antibiotics to oral therapy for CAP.

Administration, Oral↗
PubMed1998

[The management of military medical service as a scientific and academic discipline].

Scientific generalization of the medical units maintenance experience in wars and armed conflicts of the second half of the XX century and at occurrence and liquidation of consequences of the extreme situations in view of further development of the military--medical science, its differentiation and formation of new scientific disciplines and theories. Justified necessity for medical service management theory in a relatively independent branch of the military medical service--medical science. The distinctive attributes of the scientific discipline are indicated. The definitions and the structure of the object and the subject of the theory of management of the medical service are given, and new laws are formulated. The purpose, problem and contents of management of the medical service as educational discipline is determined. Some questions of coordination of its fundamental and applied parts are discussed.

Delivery of Health Care↗
PubMed1998

Blind source separation and deconvolution: the dynamic component analysis algorithm.

We derive a novel family of unsupervised learning algorithms for blind separation of mixed and convolved sources. Our approach is based on formulating the separation problem as a learning task of a spatiotemporal generative model, whose parameters are adapted iteratively to minimize suitable error functions, thus ensuring stability of the algorithms. The resulting learning rules achieve separation by exploiting high-order spatiotemporal statistics of the mixture data. Different rules are obtained by learning generative models in the frequency and time domains, whereas a hybrid frequency-time model leads to the best performance. These algorithms generalize independent component analysis to the case of convolutive mixtures and exhibit superior performance on instantaneous mixtures. An extension of the relative-gradient concept to the spatiotemporal case leads to fast and efficient learning rules with equivariant properties. Our approach can incorporate information about the mixing situation when available, resulting in a "semiblind" separation method. The spatiotemporal redundancy reduction performed by our algorithms is shown to be equivalent to information-rate maximization through a simple network. We illustrate the performance of these algorithms by successfully separating instantaneous and convolutive mixtures of speech and noise signals.

Algorithms↗
PubMed1998

Old wine in new bottles: the revival of anthralin.

Anthralin has been a consistently effective drug for the treatment of psoriasis for more than 80 years, but has not enjoyed common use in the United States because of the unwanted side effects of irritation and staining. New treatment methods such as short-contact therapy and innovative vehicle formulations minimizing these problems have allowed anthralin once again to be used effectively in psoriatic treatment programs. We review these newer adaptations and suggest that the enduring modality deserves an important place in the topical armamentarium.

Administration, Topical↗
PubMedDate not supplied

[Evidence based medicine. A new paradigm for medical practice].

Modern medical practice is an ever-changing process, and the doctor's need for information has been partially met by continuous medical education (CME) activities. It has been shown that CME activities have not prevented clinical knowledge, as well as medical practice, from deteriorating with time. When faced with the need to get the most recent and relevant information possible, the busy clinician has two major problems: most of the published medical literature is either irrelevant or not useful; and there is little time to read it. Evidence-based medicine constitutes a new paradigm for medical practice in the sense that it tries to transform clinical problems into well formulated clinical questions, selecting and critically appraising scientific evidence with predefined and rigorous rules. It combines the expertise of the individual clinician with the best external evidence from clinical research for rational, ethical and efficacious practice. Evidence-based medicine can be taught and practiced by physicians with different degrees of autonomy, with several subspecialties, working in the hospital or in outpatient clinics, alone or in groups.

Education, Medical, Continuing↗
PubMed2006

Payoff-monotonic game dynamics and the maximum clique problem.

Evolutionary game-theoretic models and, in particular, the so-called replicator equations have recently proven to be remarkably effective at approximately solving the maximum clique and related problems. The approach is centered around a classic result from graph theory that formulates the maximum clique problem as a standard (continuous) quadratic program and exploits the dynamical properties of these models, which, under a certain symmetry assumption, possess a Lyapunov function. In this letter, we generalize previous work along these lines in several respects. We introduce a wide family of game-dynamic equations known as payoff-monotonic dynamics, of which replicator dynamics are a special instance, and show that they enjoy precisely the same dynamical properties as standard replicator equations. These properties make any member of this family a potential heuristic for solving standard quadratic programs and, in particular, the maximum clique problem. Extensive simulations, performed on random as well as DIMACS benchmark graphs, show that this class contains dynamics that are considerably faster than and at least as accurate as replicator equations. One problem associated with these models, however, relates to their inability to escape from poor local solutions. To overcome this drawback, we focus on a particular subclass of payoff-monotonic dynamics used to model the evolution of behavior via imitation processes and study the stability of their equilibria when a regularization parameter is allowed to take on negative values. A detailed analysis of these properties suggests a whole class of annealed imitation heuristics for the maximum clique problem, which are based on the idea of varying the parameter during the imitation optimization process in a principled way, so as to avoid unwanted inefficient solutions. Experiments show that the proposed annealing procedure does help to avoid poor local optima by initially driving the dynamics toward promising regions in state space. Furthermore, the models outperform state-of-the-art neural network algorithms for maximum clique, such as mean field annealing, and compare well with powerful continuous-based heuristics.

Journal Article↗
PubMed1977

Use of microcapsules as timed-release parenteral dosage form: application as radiopharmaceutical imaging agent.

The development of a new type of parenteral dosage form is described. A system of microencapsulation was formulated which produced microcapsules containing a water-soluble core material. The basic microencapsulation system could be altered to produce microcapsules with varied timed-release characteristics. Tracer methodology was employed as a sensitive and versatile analytical tool for the development and evaluation of the microencapsulation system. The core material was labeled by neutron activation after microcapsule formulation, which eliminated the radiation hazard and contamination problems that could occur during formulation with a labeled core material. Both in vitro and in vivo testing showed that the release patterns of labeled core material could be altered and detected. The microcapsules developed have potential as a timed-release parenteral dosage form and as an organ-imaging radiopharmaceutical.

Animals↗
PubMed2003

A stochastic model for optimizing composite predictors based on gene expression profiles.

PURPOSE: This project was done to develop a mathematical model for optimizing composite predictors based on gene expression profiles from DNA arrays and proteomics. METHODS: The problem was amenable to a formulation and solution analogous to the portfolio optimization problem in mathematical finance: it requires the optimization of a quadratic function subject to linear constraints. The performance of the approach was compared to that of neighborhood analysis using a data set containing cDNA array-derived gene expression profiles from 14 multiple sclerosis patients receiving intramuscular inteferon-beta1a. RESULTS: The Markowitz portfolio model predicts that the covariance between genes can be exploited to construct an efficient composite. The model predicts that a composite is not needed for maximizing the mean value of a treatment effect: only a single gene is needed, but the usefulness of the effect measure may be compromised by high variability. The model optimized the composite to yield the highest mean for a given level of variability or the least variability for a given mean level. The choices that meet this optimization criteria lie on a curve of composite mean vs. composite variability plot referred to as the "efficient frontier." When a composite is constructed using the model, it outperforms the composite constructed using the neighborhood analysis method. CONCLUSIONS: The Markowitz portfolio model may find potential applications in constructing composite biomarkers and in the pharmacogenomic modeling of treatment effects derived from gene expression endpoints.

Adult↗
PubMed2005

Use of meixner functions in estimation of Volterra kernels of nonlinear systems with delay.

Volterra series representation of nonlinear systems is a mathematical analysis tool that has been successfully applied in many areas of biological sciences, especially in the area of modeling of hemodynamic response. In this study, we explored the possibility of using discrete time Meixner basis functions (MBFs) in estimating Volterra kernels of nonlinear systems. The problem of estimation of Volterra kernels can be formulated as a multiple regression problem and solved using least squares estimation. By expanding system kernels with some suitable basis functions, it is possible to reduce the number of parameters to be estimated and obtain better kernel estimates. Thus far, Laguerre basis functions have been widely used in this framework. However, research in signal processing indicates that when the kernels have a slow initial onset or delay, Meixner functions, which can be made to have a slow start, are more suitable in terms of providing a more accurate approximation to the kernels. We, therefore, compared the performance of Meixner functions, in kernel estimation, to that of Laguerre functions in some test cases that we constructed and in a real experimental case where we studied photoreceptor responses of photoreceptor cells of adult fruitflies (Drosophila melanogaster). Our results indicate that when there is a slow initial onset or delay, MBF expansion provides better kernel estimates.

Algorithms↗
PubMed1971

Optimal solutions to a linear inverse problem in geophysics.

This paper is concerned with the solution of the linear system obtained in the Backus-Gilbert formulation of the inverse problem for gross earth data. The theory of well-posed stochastic extensions to illposed linear problems, proposed by Franklin, is developed for this application. For given estimates of the statistical variance of the noise in the data, an optimal solution is obtained under the constraint that it be the output of a prescribed linear filter. Proper specification of this filter permits the introduction of information not contained in the data about the smoothness of an acceptable solution. As an example of the application of this theory, a preliminary model is presented for the density and shear velocity as a function of radius in the earth's interior.

Journal Article↗
PubMed2004

Inheritable genetic algorithm for biobjective 0/1 combinatorial optimization problems and its applications.

In this paper, we formulate a special type of multiobjective optimization problems, named biobjective 0/1 combinatorial optimization problem BOCOP, and propose an inheritable genetic algorithm IGA with orthogonal array crossover (OAX) to efficiently find a complete set of nondominated solutions to BOCOP. BOCOP with n binary variables has two incommensurable and often competing objectives: minimizing the sum r of values of all binary variables and optimizing the system performance. BOCOP is NP-hard having a finite number C(n, r) of feasible solutions for a limited number r. The merits of IGA are threefold as follows: 1) OAX with the systematic reasoning ability based on orthogonal experimental design can efficiently explore the search space of C(n, r); 2) IGA can efficiently search the space of C(n, r+/-1) by inheriting a good solution in the space of C(n, r); and 3) The single-objective IGA can economically obtain a complete set of high-quality nondominated solutions in a single run. Two applications of BOCOP are used to illustrate the effectiveness of the proposed algorithm: polygonal approximation problem (PAP) and the problem of editing a minimum reference set for nearest neighbor classification (MRSP). It is shown empirically that IGA is efficient in finding complete sets of nondominated solutions to PAP and MRSP, compared with some existing methods.

Journal Article↗
PubMedDate not supplied

Cervical orthoses: a guide to their selection and use.

A large variety of cervical orthoses is available, but these may be divided into four basic groups. Although the orthoses in each group provide similar controls, each appliance has certain discrete advantages and limitations. The effectiveness of seven different cervical appliances in restricting motion in flexion-extension, lateral bending and rotation is presented. This information may be used to rationally select an orthosis to control specific clinical problems. A guide is formulated for selecting the orthoses for the control of various cervical injuries and postoperative problems.

Adult↗
PubMed2005

Theoretical bounds of majority voting performance for a binary classification problem.

A number of earlier studies that have attempted a theoretical analysis of majority voting assume independence of the classifiers. We formulate the majority voting problem as an optimization problem with linear constraints. No assumptions on the independence of classifiers are made. For a binary classification problem, given the accuracies of the classifiers in the team, the theoretical upper and lower bounds for performance obtained by combining them through majority voting are shown to be solutions of the corresponding optimization problem. The objective function of the optimization problem is nonlinear in the case of an even number of classifiers when rejection is allowed, for the other cases the objective function is linear and hence the problem is a linear program (LP). Using the framework we provide some insights and investigate the relationship between two candidate classifier diversity measures and majority voting performance.

Algorithms↗
PubMed1994

Kinematic manipulation of molecular chains subject to rigid constraints.

We present algorithms for kinematic manipulation of molecular chains subject to fixed bond lengths and bond angles. They are useful for calculating conformations of a molecule subject to geometric constraints, such as those derived from two-dimensional NMR experiments. Other applications include searching out the full range of conformations available to a molecule such as cyclic configurations. We make use of results from robot kinematics and recently developed algorithms for solving polynomial systems. In particular, we model the molecule as a serial chain using the Denavit-Hartenberg formulation and reduce these problems to inverse kinematics of a serial chain. We also highlight the relationship between molecular embedding problems and inverse kinematics. As compared to earlier methods, the main advantages of the kinematic formulation are its generality to all molecular chains without any restrictions on the geometry and efficiency in terms of performance. The algorithms give us real time performance (order of tens of milliseconds) on smaller chains and are applicable to all chains.

Algorithms↗
PubMed1997

MEG-based imaging of focal neuronal current sources.

We describe a new approach to imaging neural current sources from measurements of the magnetoencephalogram (MEG) associated with sensory, motor, or cognitive brain activation. Many previous approaches to this problem have concentrated on the use of weighted minimum norm (WMN) inverse methods. While these methods ensure a unique solution, they do not introduce information specific to the MEG inverse problem, often producing overly smoothed solutions and exhibiting severe sensitivity to noise. We describe a Bayesian formulation of the inverse problem in which a Gibbs prior is constructed to reflect the sparse focal nature of neural current sources associated with evoked response data. We demonstrate the method with simulated and experimental phantom data, comparing its performance with several WMN methods.

Bayes Theorem↗
PubMed1992

Very brief psychotherapy in the psychiatric consultation setting.

Very brief psychotherapy has emerged as a unique treatment modality in recent years. The limited time frame dictates flexibility in the choice of therapeutic technique, but there exists a need for an assessment model to link specific technique with the clinical problem. An early psychotherapeutic formulation containing three parts is the central component of the assessment model: theoretical description of the problem, immediate goal, and intervention technique. Various theories of psychopathology and therapeutic techniques can be simultaneously applied to the clinical problem. Three cases illustrate the use of this model in a consultation/liaison setting.

Adult↗