| 1. |
- Egelberg, Peter, et al.
(författare)
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Assessing cereal grain quality with a fully automated instrument using artificial neural network processing of digitized color video images
- 1995
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Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - 0819416789 ; 2345, s. 146-158
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Konferensbidrag (refereegranskat)abstract
- A fully integrated instrument for cereal grain quality assessment is presented. Color video images of grains fed onto a belt are digitized. These images are then segmented into kernel entities, which are subject to the analysis. The number of degrees of freedom for each such object is decreased to a suitable level for Artificial Neural Network (ANN) processing. Feed- forward ANN's with one hidden layer are trained with respect to desired features such as purity and flour yield. The resulting performance is compatible with that of manual human ocular inspection and alternative measuring methods. A statistical analysis of training and test set population densities is used to estimate the prediction reliabilities and to set appropriate alarm levels. The instrument containing feeder belts, balance and CCD video camera is physically separated from the 90 MHz Pentium PC computer which is used to perform the segmentation, ANN analysis and for controlling the instrument under the Unix operating system. A user-friendly graphical user interface is used to operate the instrument. The processing time for a 50 g grain sample is approximately 2 - 3 minutes.
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| 2. |
- Hede ́n, Bo, et al.
(författare)
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Artificial neural networks for recognition of electrocardiographic lead reversal
- 1995
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Ingår i: American Journal of Cardiology. - 0002-9149. ; 75:14, s. 929-933
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Tidskriftsartikel (refereegranskat)abstract
- Misplacement of electrodes during the recording of an electrocardiogram (ECG) can cause an incorrect interpretation, misdiagnosis, and subsequent lack of proper treatment. The purpose of this study was twofold: (1) to develop artificial neural networks that yield peak sensitivity for the recognition of right/left arm lead reversal at a very high specificity; and (2) to compare the performances of the networks with those of 2 widely used rule-based interpretation programs. The study was based on 11,009 ECGs recorded in patients at an emergency department using computerized electrocardiographs. Each of the ECGs was used to computationally generate an ECG with right/left arm lead reversal. Neural networks were trained to detect ECGs with right/left arm lead reversal. Different networks and rule-based criteria were used depending on the presence or absence of P waves. The networks and the criteria all showed a very high specificity (99.87% to 100%). The neural networks performed better than the rule-based criteria, both when P waves were present (sensitivity 99.1%) or absent (sensitivity 94.5%). The corresponding sensitivities for the best criteria were 93.9% and 39.3%, respectively. An estimated 300 million ECGs are recorded annually in the world. The majority of these recordings are performed using computerized electrocardiographs, which include algorithms for detection of right/left arm lead reversals. In this study, neural networks performed better than conventional algorithms and the differences in sensitivity could result in 100,000 to 400,000 right/left arm lead reversals being detected by networks but not by conventional interpretation programs.
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| 3. |
- Hedén, Bo, et al.
(författare)
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Agreement between artificial neural networks and experienced electrocardiographer on electrocardiographic diagnosis of healed myocardial infarction
- 1996
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Ingår i: Journal of the American College of Cardiology. - 0735-1097. ; 28:4, s. 1012-1016
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Tidskriftsartikel (refereegranskat)abstract
- Objectives. The purpose of this study was to compare the diagnoses of healed myocardial infarction made from the 12-lead electrocardiogram (ECG) by artificial neural networks and an experienced electrocardiographer. Background. Artificial neural networks have proved of value in pattern recognition tasks. Studies of their utility in ECG interpretation have shown performance exceeding that of conventional ECG interpretation programs. The latter present verbal statements, often with an indication of the likelihood for a certain diagnosis, such as 'possible left ventricular hypertrophy'. A neural network presents its output as a numeric value between 0 and 1; however, these values can be interpreted as Bayesian probabilities. Methods. The study was based on 351 healthy volunteers and 1,313 patients with a history of chest pain who had undergone diagnostic cardiac catheterization. A 12-lead ECG was recorded in each subject. An expert electrocardiographer classified the ECGs in five different groups by estimating the probability of anterior myocardial infarction. Artificial neural networks were trained and tested to diagnose anterior myocardial infarction. The network outputs were divided into five groups by using the output values and four thresholds between 0 and 1. Results. The neural networks diagnosed healed anterior myocardial infarctions at high levels of sensitivity and specificity. The network outputs were transformed to verbal statements, and the agreement between these probability estimates and those of an expert electrocardiographer was high. Conclusions. Artificial neural networks can be of value in automated interpretation of ECGs in the near future.
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| 4. |
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| 5. |
- Holst, Holger, et al.
(författare)
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A confident decision support system for interpreting electrocardiograms
- 1999
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Ingår i: Clinical Physiology. - : Wiley. - 0144-5979. ; 19:5, s. 410-418
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Tidskriftsartikel (refereegranskat)abstract
- Computer-aided interpretation of electrocardiograms (ECGs) is widespread but many physicians hesitate to rely on the computer, because the advice is presented without information about the confidence of the advice. The purpose of this work was to develop a method to validate the advice of a computer by estimating the error of an artificial neural network output. A total of 1249 ECGs, recorded with computerized electrocardiographs, on patients who had undergone diagnostic cardiac catheterization were studied. The material consisted of two groups, 414 patients with and 835 without anterior myocardial infarction. The material was randomly divided into three data sets. The first set was used to train an artificial neural network for the diagnosis of anterior infarction. The second data set was used to calculate the error of the network outputs. The last data set was used to test the network performance and to estimate the error of the network outputs. The performance of the neural network, measured as the area under the receiver operating characteristic (ROC) curve, was 0.887 (0.845-0.922). The 25% test ECGs with the lowest error estimates had an area under the ROC curve as high as 0.995 (0.982-1.000), i.e. almost all of these ECGs were correctly classified. Neural networks can therefore be trained to diagnose myocardial infarction and to signal when the advice is given with great confidence or when it should be considered more carefully. This method increases the possibility that artificial neural networks will be accepted as reliable decision support systems in clinical practice.
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| 6. |
- Häkkinen, Jari, et al.
(författare)
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A Potts Neuron Approach to Communication Routing
- 1998
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Ingår i: Neural Computation. - : MIT Press - Journals. - 1530-888X .- 0899-7667. ; 10, s. 1587-1599
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Tidskriftsartikel (refereegranskat)abstract
- A feedback neural network approach to communication routing problems is developed, with emphasis on Multiple Shortest Path problems, with several requests for transmissions between distinct start- and endnodes. The basic ingredients are a set of Potts neurons for each request,with interactions designed to minimize path lengths and to prevent overloading of network arcs. The topological nature of the problem is conveniently handled using a propagator matrix approach. Although the constraints are global, the algorithmic steps are based entirely on local information, facilitating distributed implementations. In the polynomially solvable single-request case, the approach reduces to a fuzzy version of the Bellman-Ford algorithm. The method is evaluated for synthetic problems of varying sizes and load levels, by comparing to exact solutions from a branch-and-bound method, or to approximate solutions from a simple heuristic. With very few exceptions, the Potts approach gives legal solutions of very high quality. The computational demand scales merely as the product of the numbers of requests, nodes, and arcs.
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| 7. |
- Irbäck, Anders, et al.
(författare)
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Identification of amino acid sequences with good folding properties in an off-lattice model
- 1997
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Ingår i: Physical Review E. - 1063-651X. ; 55:1 SUPPL. B, s. 860-867
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Tidskriftsartikel (refereegranskat)abstract
- Folding properties of a two-dimensional toy protein model containing only two amino acid types, hydrophobic and hydrophilic, respectively, are analyzed. An efficient Monte Carlo procedure is employed to ensure that the ground states are found. The thermodynamic properties are found to be strongly sequence dependent in contrast to the kinetic ones. Hence, criteria for good folders are defined entirely in terms of thermodynamic fluctuations. With these criteria sequence patterns that fold well are isolated. For 300 chains with 20 randomly chosen binary residues approximately 10% meet these criteria. Also, an analysis is performed by means of statistical and artificial neural network methods from which it is concluded that the folding properties can be predicted to a certain degree given the binary numbers characterizing the sequences.
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| 8. |
- Irbäck, Anders, et al.
(författare)
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Local interactions and protein folding : A three-dimensional off-lattice approach
- 1997
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Ingår i: Journal of Chemical Physics. - : AIP Publishing. - 0021-9606 .- 1089-7690. ; 107:1, s. 273-282
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Tidskriftsartikel (refereegranskat)abstract
- The thermodynamic behavior of a three-dimensional off-lattice model for protein folding is probed. The model has only two types of residues, hydrophobia and hydrophilic. In absence of local interactions, native structure formation does not occur for the temperatures considered. By including sequence independent local interactions, which qualitatively reproduce local properties of functional proteins, the dominance of a native state for many sequences is observed. As in lattice model approaches, folding takes place by gradual compactification, followed by a sequence dependent folding transition. Our results differ from lattice approaches in that bimodal energy distributions are not observed and that high folding temperatures are accompanied by relatively low temperatures for the peak of the specific heat. Also, in contrast to earlier studies using lattice models, our results convincingly demonstrate that one does not need more than two types of residues to generate sequences with good thermodynamic folding properties in three dimensions.
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| 9. |
- Irbäck, Anders, et al.
(författare)
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Monte Carlo procedure for protein design
- 1998
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Ingår i: Physical Review E. - 1063-651X. ; 58:5
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Tidskriftsartikel (refereegranskat)abstract
- A method for sequence optimization in protein models is presented. The approach, which has inherited its basic philosophy from recent work by Deutsch and Kurosky [Phys. Rev. Lett. 76, 323 (1996)] by maximizing conditional probabilities rather than minimizing energy functions, is based upon a different and very efficient multisequence Monte Carlo scheme. By construction, the method ensures that the designed sequences represent good folders thermodynamically. A bootstrap procedure for the sequence space search is devised making very large chains feasible. The algorithm is successfully explored on the two-dimensional HP model [K. F. Lau and K. A. Dill, Macromolecules 32, 3986 (1989)] with chain lengths N= 16, 18, and 32.
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| 10. |
- Jönsson, Bo, et al.
(författare)
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Titrating polyelectrolytes - Variational calculations and Monte Carlo simulations
- 1996
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Ingår i: Journal of Physical Chemistry. - : American Chemical Society (ACS). - 0022-3654 .- 1541-5740. ; 100:1, s. 409-417
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Tidskriftsartikel (refereegranskat)abstract
- Variational methods are used to calculate structural and thermodynamical properties of a titrating polyelectrolyte in a discrete representation. In the variational treatment, the Coulomb potentials are emulated by harmonic repulsive forces between all monomers; the force constants are used as variational parameters. The accuracy of the variational approach is tested against Monte Carlo data. Excellent agreement is obtained for the end-to-end separation and the apparent dissociation constant for the unscreened Coulomb chain. The short-range screened Coulomb potential is more difficult to handle variationally, and its structural features are less well described, although the thermodynamic properties are predicted with the same accuracy as for the unscreened chain. The number of variational parameters is on the order of N2, where N is the number of monomers, and the computational effort scales like N3. In addition, a simplified variational procedure with only two parameters is pursued, based on a rigid-rod approximation of the polymer. It gives surprisingly good accuracy for certain physical properties.
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