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2008 AAAI Fall Symposium

作者： Tavakolian, Kouhyar Akhbardeh, Alireza Kaminska, Bozena School of Engineering Science Simon Fraser University 8888 University Drive Burnaby BC V5A 1S6 Canada Center for Cardiovascular Modeling and Bioinformatics Whiting School of Engineering Johns Hopkins University Baltimore MD 21218 United States

ISBN: (纸本)9781577353942

A novel objective methodology is proposed for the assessment of the physiological age of the heart which is based on extraction of wavelet features from sternal ballistocardiogram and classification of these features using neural networks and k-nearest neighbor classifiers. Some promising preliminary results suggest that the proposed methodology is feasible to be developed to a tool for assessment of the physiological age of the heart independent of its chronological age and present a new tool for the assessment of the cardiac performance.

关键词： Heart

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Two-step mechanism of induction of the gene expression of a prototypic cancer-protective enzyme by diphenols

Two-step mechanism of induction of the gene expression of a ...

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第14届国际自由基学术大会

作者： René V. Bensasson Vincent Zoete Albena T. Dinkova-Kostova Paul Talalay Laboratoire de Chimie des Substances Naturelles MNHN USM 0502/UMR 5154 CNRS Case 54 63 rue Buffon F 75005 Paris France Swiss Institute of Bioinformatics Molecular Modeling Group BEP-UNIL CH-1015 Lausanne Switzerland Department of Pharmacology and Molecular Sciences Johns Hopkins University School of Medicine Baltimore MD 21205 USA

Cancer-preventive activity by exogenous molecules can be mediated by enhancing the expression of cytoprotective enzymes [e.g, glutathione-S-transferase (GST) or 1 (NAD(P)H- quinone oxidoreductase NQO1)] via antioxidan... 详细信息

关键词： Two-step mechanism of induction of the gene expression of a prototypic cancer-protective enzyme by diphenols

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A Plea for the Usefulness of the Deductive Interpretation of Fuzzy Rules in Engineering Applications

A Plea for the Usefulness of the Deductive Interpretation of...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Ulrich Bodenhofer Martina Dankova Martin Stepnicka Vilem Novak The Institute of Bioinformatics Johannes Kepler University Linz Linz Austria Institute for Research and Applications of Fuzzy Modeling University of Ostrava Ostrava Czech Republic

This contribution is intended as a position paper that favors the viewpoint that inference based on deductive rules (i.e., the rules are interpreted using fuzzy implication) can indeed be considered as a valuable inference scheme in real-world applications. For this purpose, we highlight the basic concepts behind the most common fuzzy inference schemes and demonstrate their interpretation by means of illustrative examples. We conclude that, under some reasonable conditions, deductive inference is able to compete with or even outperform the well-known Mamdani-Assilian inference.

关键词： Fuzzy sets Fuzzy systems Takagi-Sugeno model Fuzzy control Bismuth Fuzzy logic bioinformatics Application software Software systems

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Providing Statistical Measures of Reliability for Body Core Temperature Predictions

Providing Statistical Measures of Reliability for Body Core ...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Andrei V. Gribok Mark J. Buller Reed W. Hoyt Jaques Reifman Nuclear Engineering Department University of Tennessee Knoxville USA Telemedicine and Advanced Technology Research Center (TATRC) U.S. Army Medical Research and Materiel Command (USAMRMC) Bioinformatics Cell Frederick MD USA U. S. Army Research Institute of Environmental Medicine Natick MA USA Chief of Biophysics and Biomedical Modeling Division of USARIEM Natick MA USA TATRC USAMRMC Biotechnology High Performance Computing Software Applications Institute Fort Detrick MD USA

This paper describes the use of a data-driven autoregressive integrated moving average model to predict body core temperature in humans during physical activity. We also propose a bootstrap technique to provide a measure of reliability of such predictions in the form of prediction intervals. We investigate the model's predictive capabilities and associated reliability using two distinct datasets, both obtained in the field under different environmental conditions. One dataset is used to develop the model, and the other one, containing an example of heat illness, is used to test the model. We demonstrate that accurate and reliable predictions of an extreme core temperature value of 39.5 degC, can be made 20 minutes ahead of time, even when the predictive model is developed on a different individual having core temperatures within healthy physiological limits. This result suggests that data-driven models can be made portable across different core temperature levels and across different individuals. Also, we show that the bootstrap prediction intervals cover the actual core temperature, and that they exhibit intuitively expected behavior as a function of the prediction horizon and the core temperature variability.

关键词： Temperature distribution Predictive models Biomedical monitoring Injuries Biological system modeling Humans Temperature sensors Biomedical measurements Military computing Testing

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Diffeomorphic matching of diffusion tensor images

Diffeomorphic matching of diffusion tensor images

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2006 Conference on Computer Vision and Pattern Recognition Workshops

作者： Cao, Yan Miller, Michael I. Mori, Susumu Winslow, Raimond L. Younes, Laurent Center for Imaging Science Johns Hopkins University Department of Radiology Johns Hopkins University School of Medicine Center for Cardiovascular Bioinformatics and Modeling Whitaker Biomedical Engineering Institute Johns Hopkins University

ISBN: (纸本)0769526462

This paper proposes a method to match diffusion tensor magnetic resonance images (DT-MRI) through the large deformation diffeomorphic metric mapping of tensor fields on the image volume, resulting in optimizing for geodesies on the space of diffeomorphisms connecting two diffusion tensor images. A coarse to fine multi-resolution and multikernel-width scheme is detailed, to reduce both ambiguities and computation load. This is illustrated by numerical experiments on DT-MRI brain and images. © 2006 IEEE.

关键词： Pattern matching

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Constructing gene expression-based diagnostic rules for understanding individualized etiology of heart failure

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Journal of Cardiothoracic-Renal Research 2006年第1期1卷 33-40页

作者： Gao, Zhong Tomaselli, Gordon Wei, Chiming Winslow, Raimond Center for Cardiovascular Bioinformatics and Modeling School of Medicine Johns Hopkins University Baltimore MD 21218 3400 North Charles Street United States Division of Cardiology School of Medicine Johns Hopkins University Baltimore MD 21205 United States Department of Surgery School of Medicine Johns Hopkins University Baltimore MD 21205 United States

Gene expression profiling has the potential to improve individualized etiology diagnosis. A statistical approach based on a multidimensional scaling (MDS) vector model is introduced to construct patient-specific rules for individualized diagnosis based on gene expression profiles. The method has a dual function of discovering new disease classes/ subclasses as well as constructing patient-specific diagnostic rules without prior knowledge of class distinction. The diagnostic rule consists of two components: (1) diagnostic gene expression pattern that suggests a critical etiological condition associated with a disease category, and (2) patient-specific correlations to the diagnostic pattern. The method is applied to construct the diagnostic rule for heart failure by which the heart failure etiology has been successfully discerned with gene expression profiles. The diagnostic rule for two potential heart failure sub-classes has been constructed to further classify heart failure patients and exploit related molecular pathogenesis. Furthermore, the diagnostic gene expression patterns reveal molecular mechanisms relevant to heart failure, and facilitate biomarker identification. The method provides an approach to exploring feasibility of gene expression profiling in individualized etiology diagnosis for therapeutic decision-making. © 2006 Asian-Pacific Cardiothoracic-Renal Association (APCRA). Published by Elsevier Ltd. All rights reserved.

关键词： Diagnostic rules Etiology Gene expression Heart failure

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Aggregation of fuzzy relations and preservation of transitivity

Aggregation of fuzzy relations and preservation of transitiv...

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International Workshops of COST Action 274 on Theory and Applications of Relational Structures as Knowledge Instruments II, TARSKI 2002-2005

作者： Saminger, Susanne Bodenhofer, Ulrich Klement, Erich Peter Mesiar, Radko Department of Knowledge-Based Mathematical Systems Johannes Kepler University A-4040 Linz Austria Institute of Bioinformatics Johannes Kepler University A-4040 Linz Austria Department of Mathematics and Descriptive Geometry Faculty of Civil Engineering Slovak University of Technology SK-813 68 Bratislava Slovakia Institute for Research and Applications of Fuzzy Modeling University of Ostrava CZ-701 03 Ostrava 1 Czech Republic

ISBN: (纸本)3540692231

This contribution provides a comprehensive overview on the theoretical framework of aggregating fuzzy relations under the premise of preserving underlying transitivity conditions. As such it discusses the related property of dominance of aggregation operators. After a thorough introduction of all necessary and basic properties of aggregation operators, in particular dominance, the close relationship between aggregating fuzzy relations and dominance is shown. Further, principles of building dominating aggregation operators as well as classes of aggregation operators dominating one of the basic t-norms are addressed. In the paper by Bodenhofer, Küng and Saminger, also in this volume, the interested reader finds an elaborated (real world) example, i.e., an application of the herein contained theoretical framework. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Mathematical operators

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Diffeomorphic Matching of Diffusion Tensor Images

Diffeomorphic Matching of Diffusion Tensor Images

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IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Yan Cao M.I. Miller S. Mori R.L. Winslow L. Younes Center for Imaging Science Johns Hopkins University USA Department of Radiology and Kennedy Krieger Institute School of Medicine Johns Hopkins University USA Center for Cardiovascular Bioinformatics & Modeling and the Whitaker Biomedical Engineering Institute Johns Hopkins University USA

This paper proposes a method to match diffusion tensor magnetic resonance images (DT-MRI) through the large deformation diffeomorphic metric mapping of tensor fields on the image volume, resulting in optimizing for geodesics on the space of diffeomorphisms connecting two diffusion tensor images. A coarse to fine multi-resolution and multikernel- width scheme is detailed, to reduce both ambiguities and computation load. This is illustrated by numerical experiments on DT-MRI brain and images.

关键词： Tensile stress Diffusion tensor imaging Biomedical imaging Optimization methods Magnetic field measurement Extraterrestrial measurements Deformable models Magnetic resonance Joining processes Geophysics computing

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Large deformation diffeomorphic metric mapping of fiber orientations

Large deformation diffeomorphic metric mapping of fiber orie...

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Proceedings - 10th IEEE International Conference on Computer Vision, ICCV 2005

作者： Cao, Yan Miller, Michael I. Winslow, Raimond L. Younes, Laurent Center for Imaging Science Johns Hopkins University Baltimore MD 21218 Center for Cardiovascular Bioinformatics and Modeling Whitaker Biomedical Engineering Institute Johns Hopkins University Baltimore MD 21218

ISBN: (纸本)076952334X

This paper proposes a method to match diffusion tensor magnetic resonance images (DT-MRI) through the large deformation diffeomorphic metric mapping of vector fields, focusing on the fiber orientations, considered as unit vector fields on the image volume. We study a suitable action of diffeomorphisms on such vector fields, and provide an extension of the Large Deformation Diffeomorphic Metric Mapping framework to this type ofdataset, resulting in optimizing for geodesies on the space of diffeomorphisms connecting two images. Two different distance function of vector fields are considered. Existence of the minimizers under smoothness assumptions on the compared vector fields is proved, and coarse to fine hierarchical strategies are detailed, to reduce both ambiguities and computation load. This is illustrated by numerical experiments on DT-MRI heart and brain images. © 2005 IEEE.

关键词： Fiber reinforced materials

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Large deformation diffeomorphic metric mapping of fiber orientations

Large deformation diffeomorphic metric mapping of fiber orie...

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International Conference on Computer Vision (ICCV)

作者： Yan Cao M.I. Miller R.L. Winslow L. Younes Center for Imaging Science Johns Hopkins University Baltimore MD USA Center for Cardiovascular Bioinformatics & Modeling and Whitaker Biomedical Engineering Institute Johns Hopkins University Baltimore MD USA

This paper proposes a method to match diffusion tensor magnetic resonance images (DT-MRI) through the large deformation diffeomorphic metric mapping of vector fields, focusing on the fiber orientations, considered as unit vector fields on the image volume. We study a suitable action of diffeomorphisms on such vector fields, and provide an extension of the large deformation diffeomorphic metric-mapping framework to this type of dataset, resulting in optimizing for geodesies on the space of diffeomorphisms connecting two images. Two different distance function of vector fields are considered. Existence of the minimizers under smoothness assumptions on the compared vector fields is proved, and coarse to fine hierarchical strategies are detailed, to reduce both ambiguities and computation load. This is illustrated by numerical experiments on DT-MRI heart and brain images

关键词： Diffusion tensor imaging Tensile stress Heart Cardiac disease Magnetic resonance imaging Image registration Biomedical imaging Biological tissues Cardiovascular diseases Cardiology

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