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Results 401 - 450 of 803
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Güler Nihal Fatma - - 2005
In this study the performance of support vector machine (SVM)and back-propagation neural network were applied to analyze the classification of the electromyogram (EMG) signals obtained from normal, neuropathy and myopathy subjects. By using autoregressive (AR) modeling, AR coefficients were obtained from EMG signals. Moreover, the support vector machine and artificial ...
Sadatsafavi M - - 2005
Artificial neural networks (ANN) are promising tools in learning complex interplay of factors on a particular outcome. We performed this study to compare the predictive power of ANN and conventional methods in prediction of bone mineral density (BMD) in Iranian post-menopausal women. A database of 10 input variables from 2158 ...
Fuller J Joseph - - 2005
TRISS is a statistical method for predicting the probability of survival of trauma victims. Analysis of data from the Trauma Registry at Charleston Area Medical Center showed that only 48% of the trauma fatalities in the 5-year period 1992-1996 were correctly predicted by TRISS. Trauma practitioners from other Trauma Centers ...
Jalali-Heravi Mehdi - - 2005
The aim of this work was to explore the usefulness of empirical models and multivariate analysis techniques in predicting electrophoretic mobilities of small peptides in capillary zone electrophoresis (CZE). The data set consists of electrophoretic mobilities, measured at pH 2.5, for 125 peptides ranging in size between 2 and 14 ...
Porter Christopher R - - 2005
OBJECTIVES: To develop a model capable of predicting prostate biopsy outcomes in a large screening population, with independent validation in the referral setting. METHODS: Data from 3814 men participating in the Tyrol screening project were used to develop the model. Prospectively collected data from two independent sites in the United ...
Sato Fumiaki - - 2005
BACKGROUND: Accurate estimation of outcome in patients with malignant disease is an important component of the clinical decision-making process. To create a comprehensive prognostic model for esophageal carcinoma, artificial neural networks (ANNs) were applied to the analysis of a range of patient-related and tumor-related variables. METHODS: Clinical and pathologic data ...
Politi Ernestina - - 2005
Controlled trials in clinical psychopharmacology may fail to provide reliable information about the benefit of treatment for the patient when considered in a real-life setting rather than as a part of a well-defined sampling procedure. Previously, we applied the mathematical model of an artificial neural network (ANN) to a pool ...
Ciosek P - - 2005
A novel strategy of data analysis for artificial taste and odour systems is presented in this work. It is demonstrated that using a supervised method also in feature extraction phase enhances fruit juice classification capability of sensor array developed at Warsaw University of Technology. Comparison of direct processing (raw data ...
Paul P A - - 2005
ABSTRACT Regression and artificial neural network (ANN) modeling approaches were combined to develop models to predict the severity of gray leaf spot of maize, caused by Cercospora zeae-maydis. In all, 329 cases consisting of environmental, cultural, and location-specific variables were collected for field plots in Iowa between 1998 and 2002. ...
Li Yongqiang - - 2005
The purpose of this work was to develop artificial neural networks (ANN) models to predict in vitro release kinetics of doxorubicin (Dox) delivered by sulfopropyl dextran ion-exchange microspheres. Four ANN models for responses at different time points were developed to describe the release profiles of Dox. Model selection was performed ...
Rajan Prabhakar - - 2005
PURPOSE OF REVIEW: The management of urolithiasis is a clinical challenge worldwide which may result in difficulty in diagnosis, treatment and prevention of recurrence. Artificial neural networks (ANNs) are well described adjuncts to many aspects of clinical urological practice. We review literature published in on-line Medline-citable English language journals to ...
Coppola Emery A EA - - 2005
Artificial neural networks (ANNs) were developed for accurately predicting potentiometric surface elevations (monitoring well water level elevations) in a semiconfined glacial sand and gravel aquifer under variable state, pumping extraction, and climate conditions. ANNs "learn" the system behavior of interest by processing representative data patterns through a mathematical structure analogous ...
Jouyban Abolghasem - - 2005
Artificial neural networks were used for modeling the mobility of five beta-blockers (i.e., labetalol atenolol, practolol, timolol and propranolol) in running buffer with ternary solvent background electrolyte systems containing 80 mM acetate buffer dissolved in water, methanol, ethanol and their ternary mixtures. The volume fractions of two solvents (f(2), f(3)) ...
Zhang Ya Xiong - - 2005
The prediction of migration time of electroosmotic flow (EOF) marker was achieved by applying artificial neural networks (ANN) model based on principal component analysis (PCA) and standard normal distribution simulation to the input variables. The voltage of performance, the temperature in the capillary, the pH and the ionic strength of ...
García Resúa Carlos - - 2005
PURPOSE: The TGDc-01 "PRA" (Ryazan State Instrument, Ryazan, Russia) tonometer is a new portable small-sized tonometer that measures intraocular pressure (IOP) through the eyelid. The purpose of this study is to assess the repeatability of the TGDc-01 IOP measurements by comparing them against those obtained with Goldmann tonometer and with ...
Fernández Elmer Andrés - - 2005
The National Kidney Foundation and the European Renal Association recommend routine measurement of hemodialysis (HD) dose and have set standards for adequacy of treatment. We compare the results of five methods for HD dose estimation, classifying each result as adequate or inadequate on the basis of equilibrated (eq) Urea Reduction ...
May A - - 2005
BACKGROUND AND STUDY AIMS: This study was conducted to test a method of measuring the depth of insertion into the small bowel during push-and-pull enteroscopy using the Erlangen Endo-Trainer. Furthermore, the Erlangen Endo-Trainer model for training in the new method of push-and-pull enteroscopy using the double-balloon technique was also evaluated. ...
Chung S W - - 2005
A seasonal occurrence of high ammonia nitrogen (NH3-N) concentrations has hampered chemical treatment processes of a water plant in Geum river of Korea. Monthly flow allocation from upstream dam is important for downstream NH3-N control. In this study, water quality models based on multiple regression (MR) and artificial neural network ...
Razavi Amir Reza - - 2005
Data mining methods can be used for extracting specific medical knowledge such as important predictors for recurrence of breast cancer in pertinent data material. However, when there is a huge quantity of variables in the data material it is first necessary to identify and select important variables. In this study ...
Yi Kim Jung - - 2005
There are many studies about cuffless and continuous blood pressure estimation using pulse transit time (PTT). In this study, we proposed the modeling method which could estimate systolic BP (SBP) conveniently and indirectly using PTT and some biometric parameters. 45 people participated in this study and we measured PTT using ...
Dong Ning - - 2005
AIM: To discriminate between fentanyl derivatives with high and low activities. METHODS: The support vector classification (SVC) method, a novel approach, was employed to investigate structure-activity relationship (SAR) of fentanyl derivatives based on the molecular descriptors, which were quantum parameters including DeltaE [energy difference between highest occupied molecular orbital energy ...
Tateda Masafumi - - 2005
The new turning method was proposed and verified its effectiveness to pathogens by laboratory scale experiments. Considering the results obtained from the previous studies, it could be said that turning of a composting pile was essential in terms of hygienic aspects but the number of turning should be minimized. Effectiveness ...
Wolf G - - 2005
A method for non-mechanistic and non-linear modelling of complex biological processes is presented, using the example of the extractive membrane bioreactor (EMB). The model is based on artificial neural networks (ANN), which are able to predict the state of the process from a combination of reactor operational parameters and natural ...
Fan Fei-Yan - - 2005
The purpose of this paper is to apply BP ANN to the discrimination of three kinds of subjects (clinical diagnosed 62 schizophrenic patients, 48 depressive patients and 26 normal controls) respectively in resting state with eyes closed and three cognitive tasks, with EEG complexity measures used as feature vectors. EEG ...
Schulze F H - - 2005
An Artificial Neural Network (ANN) is nowadays recognized as a very promising tool for relating input data to output data. It is said that the possibilities of artificial neural networks are unlimited. Here we focus on the potential role of neural networks in integrated water management. An Artificial Neural Network ...
Barua Miroslava - - 2005
Impulse Oscillometry (IOS) is an innovative patient-friendly pulmonary testing technique which measures the respiratory system impedance (Z) by using the spectral components of pressure to flow ratio which yields resistance and reactance values at different frequencies. The high dimensionality of IOS measurement data makes the analysis of this information difficult. ...
Wu Hongfa - - 2005
Scoliosis is a common and poorly understood spinal disorder that is clinically monitored with a series of full spinal X-rays. The purpose of this study was to predict scoliosis future progression at 6- and 12-month intervals with successive spinal indices and a hybrid learning technique (i.e., the combination of fuzzy ...
Erdebil Y - - 2005
This paper describes the development of a tool to predict the severity of all-terrain vehicle (ATV) injuries using artificial neural networks (ANNs). The data was obtained from the Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP). The main objective of the study was to identify the contribution of input variables ...
Arulsudar N - - 2005
PURPOSE: We planned to optimize the effect of formulation variables on the percent drug entrapment (PDE) of the liposomes encapsulating leuprolide acetate by reverse phase evaporation method using Artificial neural network (ANN) and Multiple linear regression (MLR). METHOD: Twenty seven formulations were prepared based on 3x3 factorial design. The volume ...
Hemmateenejad Bahram - - 2005
The performances of the three novel QSAR algorithms, principal component-artificial neural network modeling method combining with three factor selection procedures named eigenvalue ranking, correlation ranking, and genetic algorithm (ER-PC-ANN, CR-PC-ANN, PC-GA-ANN, respectively), are compared by application of these model to the prediction of the carcinogenic activity of a large set ...
Eftekhar Behzad - - 2005
In recent years, outcome prediction models using artificial neural network and multivariable logistic regression analysis have been developed in many areas of health care research. Both these methods have advantages and disadvantages. In this study we have compared the performance of artificial neural network and multivariable logistic regression models, in ...
Guan Peng - - 2004
AIM: To study the application of artificial neural network (ANN) in forecasting the incidence of hepatitis A, which had an autoregression phenomenon. METHODS: The data of the incidence of hepatitis A in Liaoning Province from 1981 to 2001 were obtained from Liaoning Disease Control and Prevention Center. We used the ...
Maleki N - - 2004
An artificial neural network (ANN) model is developed for simultaneous determination of Al(III) and Fe(III) in alloys by using chrome azurol S (CAS) as the chromogenic reagent and CCD camera as the detection system. All calibration, prediction and real samples data were obtained by taking a single image. Experimental conditions ...
Jiménez L - - 2005
The influence of temperature (150-170 degrees C), pulping time (15-45 min) and soda concentration (5-10%) in the pulping of abaca on the yield, kappa, viscosity, breaking length, stretch and tear index of pulp and paper sheets, was studied. Using a factorial design to identify the optimum operating conditions, equations relating ...
Sherriff Andrea - - 2004
Artificial neural networks (ANNs) are being used increasingly for the prediction of clinical outcomes and classification of disease phenotypes. A lack of understanding of the statistical principles underlying ANNs has led to widespread misuse of these tools in the biomedical arena. In this paper, the authors compare the performance of ...
Vasiljević Tatjana - - 2004
An artificial neural network (ANN) model for the prediction of retention times in high-performance liquid chromatography (HPLC) was developed and optimized. A three-layer feed-forward ANN has been used to model retention behavior of nine phenols as a function of mobile phase composition (methanol-acetic acid mobile phase). The number of hidden ...
Soria Marcelo Abel - - 2004
Many variables and their interactions can affect a biotechnological process. Testing a large number of variables and all their possible interactions is a cumbersome task and its cost can be prohibitive. Several screening strategies, with a relatively low number of experiments, can be used to find which variables have the ...
Devillers J - - 2004
Quantitative structure-toxicity relationship (QSTR) models were derived for estimating the acute oral toxicity of organophosphorus pesticides to male and female rats. The 51 chemicals of the training set and the nine compounds of the external testing set were described by means of autocorrelation vectors encoding lipophilicity, molar refractivity, H-bonding acceptor ...
Ferrante Simona - - 2004
This study falls within the ambit of research on functional electrical stimulation for the design of rehabilitation training for spinal cord injured patients. In this context, a crucial issue is the control of the stimulation parameters in order to optimize the patterns of muscle activation and to increase the duration ...
Hervás César - - 2004
The suitability of an approach for extracting heuristic rules from trained artificial neural networks (ANNs) pruned by a regularization method and with architectures designed by evolutionary computation for quantifying highly overlapping chromatographic peaks is demonstrated. The ANN input data are estimated by the Levenberg-Marquardt method in the form of a ...
Hemmateenejad Bahram - - 2004
The usefulness of the quantum chemical descriptors, calculated at the level of the RHF theory using 6-31G basis set for QSAR study of 1,4-dihydropyridine-based calcium channel antagonist was examined. A data set containing 45 dihydropyridine derivatives with known activity was used. Multiple linear regressions combined with genetic algorithm for variable ...
Francl Leonard J - - 2004
ABSTRACT Modeling in epidemiology has followed many different strategies and philosophies. Artificial neural networks (ANNs) comprise a family of highly flexible and adaptive models that have shown promise for application to modeling disease phenomena in general and plant disease forecasting in particular. ANN modeling requires the availability of representative, robust ...
Coli Pierluigi - - 2004
PURPOSE: The precision of a computer-aided design/manufacturing (CAD/CAM) system to manufacture zirconium dioxide copings with a predetermined internal space was investigated. MATERIALS AND METHODS: Two master models were produced in acrylic resin. One was directly scanned by the Decim Reader. The Decim Producer then manufactured 10 copings from prefabricated zirconium ...
Alados Inmaculada - - 2004
In recent years, there has been a substantial increase in attempts to model the flux of ultraviolet radiation (UV). UV irradiance at surface level is a result of the combined effects of solar zenith angle, surface elevation, cloud cover, aerosol load and optical properties, surface albedo and the vertical profile ...
Bhasin Manoj - - 2004
Cytotoxic T lymphocyte (CTL) epitopes are potential candidates for subunit vaccine design for various diseases. Most of the existing T cell epitope prediction methods are indirect methods that predict MHC class I binders instead of CTL epitopes. In this study, a systematic attempt has been made to develop a direct ...
Lü Q - - 2004
The hydrohaloalkanes have attracted much attention as potential substitutes of chlorofluorocarbons (CFCs) that deplete the ozone layer and lead to great high global warming. Having a short atmospheric lifetime is very important for the potential substitutes that may also induce ozone depletion and yield high global warming gases to be ...
Singh Amar Partap - - 2004
In this work, the development of an Artificial Neural Network (ANN) based soft estimator is reported for the estimation of static-nonlinearity associated with the transducers. Under the realm of ANN based transducer modeling, only two neural models have been suggested to estimate the static-nonlinearity associated with the transducers with quite ...
Linder Roland - - 2004
MOTIVATION: Human decisions often proceed in two steps. Initially those most preferred are chosen followed by a subsequent choice of these preferences. Applying one artificial neural network (ANN), a classification is limited to the preselection process. The final categorization is only possible by a subsequent ANN that distinguishes the pre-chosen ...
Li Genyuan - - 2004
A new High Dimensional Model Representation (HDMR) tool, Multicut-HDMR, is introduced and applied to an ionospheric electron density model. HDMR is a general set of quantitative model assessment and analysis tools for improving the efficiency of deducing high-dimensional input-output system behavior. HDMR describes an output [f(x)] in terms of its ...
Natt Navjyot K - - 2004
This article describes a method developed for predicting transmembrane beta-barrel regions in membrane proteins using machine learning techniques: artificial neural network (ANN) and support vector machine (SVM). The ANN used in this study is a feed-forward neural network with a standard back-propagation training algorithm. The accuracy of the ANN-based method ...
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