Bibliografías temáticas / Medicine – Mathematical models

Literatura académica sobre el tema "Medicine – Mathematical models"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 29 de enero de 2023

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Artículos de revistas sobre el tema "Medicine – Mathematical models"

1

Knapp, David y Richard Bellman. "Mathematical Models in Medicine". Mathematical Gazette 70, n.º 451 (marzo de 1986): 79. http://dx.doi.org/10.2307/3615870.

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Zietz, Stanley. "Computers and Mathematical Models in Medicine". Mathematical Biosciences 75, n.º 1 (julio de 1985): 139–40. http://dx.doi.org/10.1016/0025-5564(85)90070-7.

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Lyshchuk, V. A., D. A. Andrikov, D. SH Hazizova, O. V. Drakina, S. V. Kalyn, L. V. Sazykina y H. V. Shevchenka. "Methods of mathematical medicine". Electronics and Communications 16, n.º 3 (28 de marzo de 2011): 176–80. http://dx.doi.org/10.20535/2312-1807.2011.16.3.266442.

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The decision of the main problem for development of mathematical medicine – definitions of criteria and restrictions for synthesis and therapy optimization is proposed. The methods described here connected to elaboration of the mathematical models, control of medical treatment, individualization and use of models, allocation of pathological processes. The separation of pathological and adaptive organism reactions (homeostatic, compensatory, protective) wasn’t realized early. Methods give the possibiliy to estimate numericaly efficiency and helpfully of medicinal therapy, and also the quality of treatment. On the basis of these methods the technologies provided physicians decision of doctor have been carrying out. This technologies were successfully applied in treatment of more than 4000 serious patients
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Jódar, Lucas, Luis Acedo y Juan Carlos Cortés. "Mathematical models in medicine, business and engineering 2009". Mathematical and Computer Modelling 52, n.º 7-8 (octubre de 2010): 947–48. http://dx.doi.org/10.1016/j.mcm.2010.03.033.

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Adomian, George. "Solving the mathematical models of neurosciences and medicine". Mathematics and Computers in Simulation 40, n.º 1-2 (diciembre de 1995): 107–14. http://dx.doi.org/10.1016/0378-4754(95)00021-8.

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Kozhanov, V. S., S. O. Ustalkov y A. O. Khudoshina. "TOW CABLES MATHEMATICAL MODELS". Mathematical Methods in Technologies and Technics, n.º 5 (2022): 62–68. http://dx.doi.org/10.52348/2712-8873_mmtt_2022_5_62.

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Scherer, Almut y Angela McLean. "Mathematical models of vaccination". British Medical Bulletin 62, n.º 1 (1 de julio de 2002): 187–99. http://dx.doi.org/10.1093/bmb/62.1.187.

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Nikolova, Iveta. "On stochastic models in biology and medicine". Asian-European Journal of Mathematics 13, n.º 08 (21 de mayo de 2020): 2050168. http://dx.doi.org/10.1142/s1793557120501685.

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Stochastic models along with deterministic models are successfully used for mathematical description of biological processes. They apply knowledge from probability theory and mathematical statistics to analyze specific characteristics of living systems. The paper is devoted to some stochastic models of various phenomena in biology and medicine. Basic concepts and definitions used in classical probability models are considered and illustrated by several examples with solutions. The stochastic kinetic modeling approach is described. A new kinetic model of autoimmune disease is presented. It is a system of nonlinear partial integro-differential equations supplemented by corresponding initial conditions. The modeling problem is solved computationally.
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Dauhoo, Muhammad Zaid, Laurent Dumas y Pierre Gabriel. "CIMPA School on Mathematical Models in Biology and Medicine". ESAIM: Proceedings and Surveys 62 (2018): I. http://dx.doi.org/10.1051/proc/201862000.

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Krylov, A. P. "Mathematical modeling in modern medicine. Fields. Approaches. Problems". Terapevt (General Physician), n.º 9 (15 de agosto de 2020): 75–79. http://dx.doi.org/10.33920/med-12-2009-08.

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Tesis sobre el tema "Medicine – Mathematical models"

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Campanelli, Mark Benjamin. "Multicellular mathematical models of somitogenesis". Thesis, Montana State University, 2009. http://etd.lib.montana.edu/etd/2009/campanelli/CampanelliM0809.pdf.

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Somitogenesis is an important pattern formation process in the developmental biology of vertebrates. The phenomenon has received wide attention from experimental, theoretical, and computational biologists. Numerous mathematical models of the process have been proposed, with the clock and wavefront mechanism rising to prominence over the last ten years. This work presents two multicellular mathematical models of somitogenesis. The first is a phenomenological phase oscillator model that reproduces both the clock and wavefront aspects of somitogenesis, but lacks a biological basis. The second is a biologically informed delay differential equation model of the clock-wave that is produced by coordinated oscillatory gene expression across many cells. Careful and efficient model construction, parameter estimation, and model validation identify important nonlinear mechanisms in the genetic control circuit of the somitogenesis clock. In particular, a graded control protein combined with differential decay of clock protein monomers and dimers is found to be a key mechanism for slowing oscillations and generating experimentally observed waves of gene expression. This represents a mode of combinatorial control that has not been previously examined in somitogenesis, and warrants further experimental and theoretical investigation.
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Stekel, Dov Joseph. "Mathematical models of immune system and virus dynamics". Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.364143.

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CLOUGH, ANNE VIRGINIA. "A MATHEMATICAL MODEL OF SINGLE-PHOTON EMISSION COMPUTED TOMOGRAPHY (RADON TRANSFORM, COMPTON SCATTER, ATTENUATION, NUCLEAR MEDICINE)". Diss., The University of Arizona, 1986. http://hdl.handle.net/10150/188142.

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Single-photon emission computed tomography (SPECT) is a nuclear-medicine imaging technique that has been shown to provide clinically useful images of radionuclide distributions within the body. The problem of quantitative determination of tomographic activity images from a projection data set leads to a mathematical inverse problem which is formulated as an integral equation. The solution of this problem then depends on an accurate mathematical model as well as a reliable and efficient inversion algorithm. The effects of attenuation and Compton scatter within the body have been incorporated into the model in the hopes of providing a more physically realistic mathematical model. The attenuated Radon transform is the mathematical basis of SPECT. In this work, the case of constant attenuation is reviewed and a new proof of the Tretiak-Metz algorithm is presented. A space-domain version of the inverse attenuated Radon transform is derived. A special case of this transform that is applicable when the object is rotationally symmetric, the attenuated Abel transform is derived, and its inverse is found. A numerical algorithm for the implementation of the inverse attenuated Radon transform with constant attenuation is described and computer simulations are performed to demonstrate the results of the inversion procedure. With the use of the single-scatter approximation and an energy-windowed detector, the effects of Compton scatter are incorporated into the model. The data is then taken to be the sum of primary photons and single-scattered photons. The scattered photons are modeled by a scatter operator acting on the original activity distribution within the object where the operator consists of convolution with a given analytic kernel followed by a boundary cut-off operation. A solution is given by first applying the inverse attenuated Radon transform to the data set. This leads to a Fredholm integral equation to which a Neumann series solution is constructed. Again simulations are performed to validate the accuracy of the assumptions within the model as well as to numerically demonstrate the reconstruction procedure.
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Orme, Michelle Elaine. "The vascularization of solid tumours : mathematical models of tumour angiogenesis and vascular tumour growth". Thesis, University of Bath, 1996. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362238.

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Knight, Peter Robin. "Artificial intelligence and mathematical models for intelligent management of aircraft data". Thesis, University of Southampton, 2012. https://eprints.soton.ac.uk/355717/.

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Increasingly, large volumes of aircraft data are being recorded in an effort to adapt aircraft maintenance procedures from being time-based towards condition-based techniques. This study uses techniques of artificial intelligence and develops mathematical models to analyse this data to enable improvements to be made in aircraft management, affordability, availability, airworthiness and performance. In addition, it highlights the need to assess the integrity of data before further analysis and presents the benefits of fusing all relevant data sources together. The research effort consists of three separate investigations that were undertaken and brought together in order to provide a unified set of methods aimed at providing a safe, reliable, effective and efficient overall procedure. The three investigations are: 1. The management of helicopter Health Usage Monitoring System (HUMS) Condition Indicators (CIs) and their analysis, using a number of techniques, including adaptive thresholds and clustering. These techniques were applied to millions of CI values from Chinook HUMS data. 2. The identification of fixed-wing turbojet engine performance degradation, using anomaly detection techniques, applied to thousands of in-service engine runs from Tornado aircraft. 3. The creation of models to identify unusual aircraft behaviour, such as uncommanded flight control movements. Two Chinook helicopter systems were modelled and the models were applied to over seven hundred in-service flights. In each case, the existing techniques were directed toward a condition-based maintenance approach, giving improved detection and earlier warning of faults.
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Powell, Megan Olivia. "Mathematical Models of the Activated Immune System During HIV Infection". University of Toledo / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1301415627.

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Cargill, Ellen Bernadette. "A mathematical liver model and its application to system optimization and texture analysis". Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184936.

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This dissertation presents realistic mathematical models of normal and diseased livers and a nuclear medicine camera. The mathematical model of a normal liver is developed by creating a data set of points on the surface of the liver and fitting it to a truncated set of spherical harmonics. We model the depth-dependent MTF of a scintillation camera taking into account the effects of Compton scatter, linear attenuation, intrinsic detector resolution, collimator resolution, and Poisson noise. The differential diagnosis on a liver scan includes normal, focal disease, and diffuse disease. Object classes of normal livers are created by randomly perturbing the spherical harmonic coefficients. Object classes of livers with focal disease are created by introducing cold ellipsoids within the liver volume. Cirrhotic livers are created by modelling the gross morphological changes, heterogenous uptake, and decreased overall uptake. Simulated nuclear medicine images are made by projecting livers through nuclear imaging systems. The combination of object classes of simulated livers and models of different imaging systems is applied to imaging-system design optimization in a psycho-physical study. Human observer performance on simulated liver images made on nine different systems is compared to the Hotelling trace criterion (HTC). The system with the best observer performance is judged to be the best system. The correlation between the human performance metric dₐ and the HTC for this study was 0.829, suggesting that the HTC may have value as a predictor of observer performance. Texture in a liver scan is related to the three-dimensional distribution of functional acini, which changes with disease. One measure of texture is the fractal dimension, related to the Fourier power spectrum. We measured the average radial power spectra of 70 liver scans. All of these scans yield straight lines when plotted on a log-log scale, a characteristic of fractal objects. The slope of the line is related to the fractal dimension of the acini. The slopes are significantly higher for normal than abnormal livers (t = 4.04, df = 29, p = 0.005). On 32 liver scans with confirmed diagnoses, receiver operating characteristics (ROC) analysis was performed using power spectral slope as a feature. Analysis of the ROC curve yielded an area under the curve of 85, suggesting that power spectral slope may be a useful classifier of disease.
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Easton, Jonathan. "Mathematical models of health focusing on diabetes : delay differential equations and data mining". Thesis, Northumbria University, 2015. http://nrl.northumbria.ac.uk/23582/.

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Mathematical models have been applied to biology and health to gain a better understanding of physiological systems and disease, as well as to improve levels of treatment and care for certain conditions. This thesis will focus on two different methodologies to investigate models of health, namely delay differential equations andBayesian based data mining. The first approach uses delay differential equations to model the glucose-insulin regulation system. Many models exist in this area, typically including four exponential functions, and take a number of different forms. The model used here is a system of two delay differential equations with two time delays. The one delay form of this model has previously been widely studied, but less is known about the two delay system from an analytical view point. This work improves upon the existing models by incorporating Hill functions instead of exponential functions. The new model presented is studied for its appropriateness and robustness to changing parameters such as glucose infusion rate and insulin degradation. A local and global stability of the two-delay system is presented both in general terms and explicitly using Lyapunov functionals and linear matrix inequalities. The second method employs data mining techniques including a robust and transparent naïve Bayes classifier for classification and prediction of aspects of health. A study into prediction of post-stroke mortality is made on a data set of stroke patients. Interesting results are obtained for the classification of naturally arising mortality periods and an investigation into the role of age as a risk factor for post-stroke mortality. A wide range of risk factors are then investigated for significance which are used to build new predictive models. These two approaches have the joint aim of improving the understanding of aspects of health through mathematical modelling techniques. A new model of the glucose-insulin regulatory system is developed and for the first time an analysis of the global stability of the two-delay model by use of a Lyapunov functional is provided. The second approach sees typical and robust data mining techniques used to analyse medical data. New models for stroke mortality and prediction of diabetes and obesity are created, which review risk factors and also illustrate the benefit of data mining techniques for analysing medical data.
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9

Vogel, Vance T. "Determining personnel accession requirements for Medical Service Corps Health Care Administrators using a steady state analysis /". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Mar%5FVogel.pdf.

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Thesis (M.S. in Business Administration)--Naval Postgraduate School, March 2006.
Thesis Advisor(s): Anke Richter, Kathryn M. Kocher. Includes bibliographical references (p. 113-114 ). Also available online.
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Al-otoum, Mohammed Fawzi. "Evaluation of bootstrapping as a validation technique for population pharmacokinetic models". Scholarly Commons, 2004. https://scholarlycommons.pacific.edu/uop_etds/590.

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It has been recommended by the FDA and others that the population pharmacokinetic models (PPKM) need to be validated. This is particularly true when the model plays a key role in the construction of dosing strategies. It was the objective of the current study to evaluate the ability of bootstrapping to identify PPKMs that were estimated from data without influence observations versus PPKMs from data containing influence observations. The evaluation was performed in four phases. In phase I, ten no-influence index datasets and ten influence index datasets were created. A model parameter (theta !) was estimated for the index datasets. It was found that influence observations caused an over-estimation of the model parameter. In phase II, 200 bootstrap datasets were resampled with replacement from each of the twenty index datasets ( 4000 datasets total). In phase III, the bootstrapping validation method was executed using NONMEM for model estimation and the resulting statistics were used to detect models developed from influence data. The metrics of choice were mean absolute prediction error (MAPE) and mean squared prediction error (MSPE). In phase IV, the impact of achieving a global minimum in the NONMEM program on the non-parametric bootstrap validation process was investigated. This study showed that the current and widely followed procedure for application of the bootstrap for PPK model validation has significant deficiencies. The achievement of a global minimum in the NONMEM program proved to be an important and pivotal factor when applying bootstrapping to the PPKM validation process. Therefore, we concluded that each bootstrap dataset should be evaluated with several model control streams. Further, the suggested value for an acceptable difference between the NONMEM minimum objective function values for a global and a near global minimum should be 2.5 units.
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Libros sobre el tema "Medicine – Mathematical models"

1

Simon, William. Mathematical techniques for biology and medicine. New York: Dover Publications, 1986.

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Mathematical techniques for biology and medicine. New York: Dover Publications, 1986.

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Akram, Aldroubi y Unser Michael A, eds. Wavelets in medicine and biology. Boca Raton: CRC Press, 1996.

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Heinz, Schättler, Friedman Avner, Kashdan Eugene y SpringerLink (Online service), eds. Mathematical Methods and Models in Biomedicine. New York, NY: Springer New York, 2013.

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Mathematical modelling in biomedicine: Optimal control of biomedical systems. Dordrecht, Holland: D. Reidel Pub. Co., 1986.

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Mathematical methods and models in the biological sciences. Englewood Cliffs, N.J: Prentice Hall, 1988.

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Kawamura, Noriyuki. Kenkōdo no sokuteihō oyobi keisanshiki no kaihatsu ni kansuru kenkyū: Heisei 13-nendo sōkatsu buntan kenkyū hōkokusho. [Japan: s.n.], 2002.

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J, Hosking R. y Venturino Ezio, eds. Aspects of mathematical modelling: Applications in science, medicine, economics and management. Basel: Birkhäuser, 2008.

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Nuclear medicine applications and their mathematical basis. Singapore: World Scientific, 2011.

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Goris, Michael L. Nuclear medicine applications and their mathematical basis. Singapore: World Scientific, 2011.

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Capítulos de libros sobre el tema "Medicine – Mathematical models"

1

Zin, W. A. y R. F. M. Gomes. "Mathematical Models in Respiratory Mechanics". En Anaesthesia, Pain, Intensive Care and Emergency Medicine — A.P.I.C.E., 391–400. Milano: Springer Milan, 1996. http://dx.doi.org/10.1007/978-88-470-2203-4_34.

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Nanni, P. G., G. Castellani, P. Pettazzoni, G. Pallotti y C. Pallotti. "Limits of mathematical models in biology and medicine". En Atherosclerosis and Cardiovascular Disease, 232–36. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0731-7_31.

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Dutta, A. y A. S. Popel. "Analysis of Tissue Diffusivity Using Mathematical Models". En Advances in Experimental Medicine and Biology, 17–29. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-1875-4_3.

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Wright, Neil T. "Mathematical Models of Cell Response Following Heating". En Advances in Experimental Medicine and Biology, 279–94. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96445-4_15.

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Enright, Catherine G., Michael G. Madden, Niall Madden y John G. Laffey. "Clinical Time Series Data Analysis Using Mathematical Models and DBNs". En Artificial Intelligence in Medicine, 159–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22218-4_20.

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Eby, Wayne M. y Natalia Coleman. "Mathematical Models in Stem Cell Differentiation and Fate Predictability". En Regenerative Medicine - from Protocol to Patient, 175–222. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27583-3_6.

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Pečerska, Jūlija, James Wood, Mark M. Tanaka y Tanja Stadler. "Mathematical Models for the Epidemiology and Evolution of Mycobacterium tuberculosis". En Advances in Experimental Medicine and Biology, 281–307. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64371-7_15.

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Adam, John A. "Mathematical Models of Tumor Growth: From Empirical Description to Biological Mechanism". En Advances in Experimental Medicine and Biology, 287–300. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4419-9019-8_19.

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Lawonn, Kai y Bernhard Preim. "Feature Lines for Illustrating Medical Surface Models: Mathematical Background and Survey". En Visualization in Medicine and Life Sciences III, 93–131. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-24523-2_5.

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Zenker, S., G. Clermont y M. R. Pinsky. "Using Mathematical Models to Improve the Utility of Quantitative ICU Data". En Yearbook of Intensive Care and Emergency Medicine, 479–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-49433-1_43.

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Actas de conferencias sobre el tema "Medicine – Mathematical models"

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Chrobak, Joanna M., Henar Herrero, Alberto Cabada, Eduardo Liz y Juan J. Nieto. "Mathematical model of cancer with competition". En MATHEMATICAL MODELS IN ENGINEERING, BIOLOGY AND MEDICINE: International Conference on Boundary Value Problems: Mathematical Models in Engineering, Biology and Medicine. AIP, 2009. http://dx.doi.org/10.1063/1.3142956.

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Chilbert, M., J. Myklebust, T. Prieto, T. Swiontek y A. Sances. "Mathematical models of electrical injury". En Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1988. http://dx.doi.org/10.1109/iembs.1988.94632.

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Aleixo, Sandra M., J. Leonel Rocha, Dinis D. Pestana, Alberto Cabada, Eduardo Liz y Juan J. Nieto. "Populational Growth Models Proportional to Beta Densities with Allee Effect". En MATHEMATICAL MODELS IN ENGINEERING, BIOLOGY AND MEDICINE: International Conference on Boundary Value Problems: Mathematical Models in Engineering, Biology and Medicine. AIP, 2009. http://dx.doi.org/10.1063/1.3142952.

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El-Shahed, Moustafa, Alberto Cabada, Eduardo Liz y Juan J. Nieto. "Positive Solutions for Boundary Value Problems of Nonlinear Fractional Differential Equations". En MATHEMATICAL MODELS IN ENGINEERING, BIOLOGY AND MEDICINE: International Conference on Boundary Value Problems: Mathematical Models in Engineering, Biology and Medicine. AIP, 2009. http://dx.doi.org/10.1063/1.3142922.

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Enatsu, Yoichi, Alberto Cabada, Eduardo Liz y Juan J. Nieto. "Permanence for multi-species nonautonomous Lotka-Volterra cooperative systems". En MATHEMATICAL MODELS IN ENGINEERING, BIOLOGY AND MEDICINE: International Conference on Boundary Value Problems: Mathematical Models in Engineering, Biology and Medicine. AIP, 2009. http://dx.doi.org/10.1063/1.3142923.

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Enguiça, Ricardo, Luís Sanchez, Alberto Cabada, Eduardo Liz y Juan J. Nieto. "A second order non-autonomous problem on the half-line: a variational approach". En MATHEMATICAL MODELS IN ENGINEERING, BIOLOGY AND MEDICINE: International Conference on Boundary Value Problems: Mathematical Models in Engineering, Biology and Medicine. AIP, 2009. http://dx.doi.org/10.1063/1.3142924.

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Fabião, Fátima, Maria do Rosário Grossinho, Onofre Simões, Alberto Cabada, Eduardo Liz y Juan J. Nieto. "Solvability of a stationary nonlinear Black-Scholes equation under conditions on the potential". En MATHEMATICAL MODELS IN ENGINEERING, BIOLOGY AND MEDICINE: International Conference on Boundary Value Problems: Mathematical Models in Engineering, Biology and Medicine. AIP, 2009. http://dx.doi.org/10.1063/1.3142925.

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Faria, Teresa, Alberto Cabada, Eduardo Liz y Juan J. Nieto. "Global Stability and Singularities for Lotka-Volterra Systems with Delays". En MATHEMATICAL MODELS IN ENGINEERING, BIOLOGY AND MEDICINE: International Conference on Boundary Value Problems: Mathematical Models in Engineering, Biology and Medicine. AIP, 2009. http://dx.doi.org/10.1063/1.3142926.

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Webb, J. R. L., Alberto Cabada, Eduardo Liz y Juan J. Nieto. "Higher order non-local (n−1,1) conjugate type boundary value problems". En MATHEMATICAL MODELS IN ENGINEERING, BIOLOGY AND MEDICINE: International Conference on Boundary Value Problems: Mathematical Models in Engineering, Biology and Medicine. AIP, 2009. http://dx.doi.org/10.1063/1.3142949.

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Allahviranloo, T., N. Ahmady, E. Ahmady, Alberto Cabada, Eduardo Liz y Juan J. Nieto. "Improved Predictor Corrector Method for solving fuzzy initial value problem". En MATHEMATICAL MODELS IN ENGINEERING, BIOLOGY AND MEDICINE: International Conference on Boundary Value Problems: Mathematical Models in Engineering, Biology and Medicine. AIP, 2009. http://dx.doi.org/10.1063/1.3142927.

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