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arXiv 2023年

作者： Schicktanz, Silke Welsch, Johannes Schweda, Mark Hein, Andreas Rieger, Jochem W. Kirste, Thomas University Medical Center Göttingen Dept. for Medical Ethics and History of Medicine Germany University of Oldenburg Department of Health Services Research Division for Ethics in Medicine Germany University of Oldenburg Department of Health Services Research Division Assistance Systems and Medical Device Technology Germany University of Oldenburg Applied Neurocognitive Psychology Lab Germany University of Rostock Institute for Visual and Analytic Computing Germany Hanse-Wissenschaftskolleg Institute of Advance Studies Germany

Current ethical debates on the use of artificial intelligence (AI) in health care treat AI as a product of technology in three ways. First, by assessing risks and potential benefits of currently developed AI-enabled products with ethical checklists;second, by proposing ex ante lists of ethical values seen as relevant for the design and development of assisting technology, and third, by promoting AI technology to use moral reasoning as part of the automation process. The dominance of these three perspectives in the discourse is demonstrated by a brief summary of the literature and by findings our own expert interviews regarding their views on intelligent assistive technology in dementia care which is a particular focus of our approach. Subsequently, we propose a fourth approach to AI, namely as a methodological tool to assist ethical reflection. We provide a concept of an AI-simulation informed by three separate elements: 1) stochastic human behavior models based on behavioral data for simulating realistic settings, 2) qualitative empirical data on value statements regarding internal policy, and 3) visualization components that aid in understanding the impact of changes in these variables. The potential of this approach is to inform an interdisciplinary field about anticipated ethical challenges or ethical trade-offs in concrete settings and, hence, to spark a re-evaluation of design and implementation plans. This may be particularly useful for applications that deal with extremely complex values and behavior or with limitations on the communication resources of affected persons (e.g., persons with dementia care or for care of persons with cognitive impairment). Simulation does not replace ethical reflection but does allow for detailed, context-sensitive analysis during the design process and prior to implementation. Finally, we discuss the inherently quantitative methods of analysis afforded by stochastic simulations as well as the potential for ethical discussions

关键词： Stochastic systems

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Teaching a Modeling Process: Reflections from An Online Course

Teaching a Modeling Process: Reflections from An Online Cour...

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2021 Winter Simulation Conference, WSC 2021

作者： Bijak, Jakub Hilton, Jason Hinsch, Martin Lipscombe, Kim Nurse, Sarah Prike, Toby Smith, Peter W.F. Reinhardt, Oliver Uhrmacher, Adelinde M. Higham, Philip A. Grow, Andre University of Southampton Highfield Campus Department of Social Statistics and Demography SouthamptonSO17 1BJ United Kingdom Institute for Visual and Analytic Computing University of Rostock Rostock18059 Germany School of Psychology University of Southampton Highfield Campus SouthamptonSO17 1BJ United Kingdom Max Planck Institute for Demographic Research Rostock18057 Germany

ISBN: (纸本)9781665433112

The outbreak of the COVID-19 pandemic in 2020 posed unique challenges for academic and professional education, while at the same time offering opportunities related to the mass switching of the delivery of courses to the online mode. In this paper, we share the experience of organizing and delivering an online doctoral-level course on Agent-Based Modeling for Social Research. Our aim was to teach interdisciplinary content on various elements of the modeling process in a coherent and practical way. In the paper, we offer a critical assessment of different aspects of the course, related to content as well as organization and delivery. By looking at the course in the light of the current knowledge on good teaching and learning practices from the educational and psychological literature, and reflecting on the lessons learned, we offer a blueprint for designing and running complex, multi-thread simulation courses in an efficient way. © 2021 IEEE.

关键词： Teaching

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Optimizing Discrete Simulations of the Spread of HIV-1 to Handle Billions of Cells on a Workstation 20

Optimizing Discrete Simulations of the Spread of HIV-1 to Ha...

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2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, SIGSIM-PADS 2020

作者： Giabbanelli, Philippe J. Devita, Joshua A. Köster, Till Kohrt, Jared A. Miami University Department of Computer Science and Software Engineering OxfordOH United States Department of Computer Science Northern Illinois University DeKalb IL United States University of Rostock Institute for Visual and Analytic Computing Rostock Germany Furman University Computer Science Department GreenvilleSC United States

ISBN: (纸本)9781450375924

Cellular Automata have been used on many occasions to model the spread of the Human Immunodeficiency Virus (HIV) within a human body. This is in part due to the relative simplicity of crafting their rules and the convenience of visualizing disease dynamics in 2D. Although such models appeared in 2001 and have been extended in dozens of studies, their potential to serve as a virtual laboratory has been limited by their computationally intensive nature. So far, they have been used to simulate at most 0.5 million cells instead of the billion cells that may harbor the virus. Simulating too few cells is a key issue for calibration (the 'small' models are calibrated based on results observed in a much larger space), prevents us from using a sufficient proportion of cells to model latent HIV reservoirs (in which HIV can hide for years), and prohibits even more computationally intensive aspects such as tracking mutations (which is essential to assess drug resistance). In short, the low number of cells prevents these models from answering many of the questions that would make them useful as virtual laboratories. Although the models may be scaled by running on clusters, this is not always an option since interdisciplinary research in discrete models of HIV often takes place on the lab's computer, and patients for whom we seek to provide virtual laboratories may have limited access to computational resources. Given these constraints, we demonstrate how to optimize simulations of HIV on a workstation by combining features such as just-in-time compilation, parallelism at the level of threads, pseudo random number generators, and simplified handling of neighbors in a cellular automaton. Our results demonstrate that, within 10 minutes, we can finish a simulation run for 6.7 billion cells instead of 60,000 cells in an unoptimized simulation. © 2020 Association for computing Machinery.

关键词： Cells

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Towards Accurate visualization and Measurement of Localized Changes in Intraretinal Layer Thickness

Towards Accurate Visualization and Measurement of Localized ...

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IEEE Workshop on visual analytics in Healthcare (VAHC)

作者： Martin Röhlig Christoph Schmidt Ruby Kala Prakasam Oliver Stachs Heidrun Schumann Institute of Visual and Analytic Computing University of Rostock Department of Ophthalmology University of Rostock

Optical coherence tomography (OCT) enables high-resolution 3D imaging of intraretinal layers. The layers' thickness are commonly compared to normative data to understand a variety of retinal and systemic disorders. Yet, discovering and measuring localized thickness differences in the complex OCT data is challenging, particularly in an early stage of eye diseases. We combine interactive visualization and automated measurements to support the analysis of abnormal layer thickness. First, the spatial distribution of thickness differences is visualized via precise deviation maps. Second, statistical tests are applied to quantify every point of the visualized data. Third, measurements of significant differences for anatomically distinct areas and selected regions of interest are retrieved. We demonstrate the effectiveness of our solution in detecting abnormal layer thickness in the context of a cross-sectional ophthalmic study.

关键词： Retina Area measurement Thickness measurement Data visualization Diseases Diabetes Image color analysis

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ProHap Explorer: visualizing Haplotypes in Proteogenomic Datasets

arXiv

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arXiv 2025年

作者： Vašíček, Jakub Skiadopoulou, Dafni Kuznetsova, Ksenia G. Käll, Lukas Vaudel, Marc Bruckner, Stefan Mohn Center for Diabetes Precision Medicine Department of Clinical Science University of Bergen Bergen Norway Computational Biology Unit Department of Informatics University of Bergen Bergen Norway Metabolism Program Broad Institute of MIT and Harvard CambridgeMA United States Science for Life Laboratory Department of Gene Technology KTH - Royal Institute of Technology Stockholm Sweden Department of Genetics and Bioinformatics Health Data and Digitalization Norwegian Institute of Public Health Oslo Norway Institute for Visual and Analytic Computing University of Rostock Rostock Germany

In mass spectrometry-based proteomics, experts usually project data onto a single set of reference sequences, overlooking the influence of common haplotypes (combinations of genetic variants inherited together from a parent). We recently introduced ProHap, a tool for generating customized protein haplotype databases. Here, we present ProHap Explorer, a visualization interface designed to investigate the influence of common haplotypes on the human proteome. It enables users to explore haplotypes, their effects on protein sequences, and the identification of non-canonical peptides in public mass spectrometry datasets. The design builds on well-established representations in biological sequence analysis, ensuring familiarity for domain experts while integrating novel interactive elements tailored to proteogenomic data exploration. User interviews with proteomics experts confirmed the tool's utility, highlighting its ability to reveal whether haplotypes affect proteins of interest. By facilitating the intuitive exploration of proteogenomic variation, ProHap Explorer supports research in personalized medicine and the development of targeted therapies. © 2025, CC BY.

关键词： Proteomics

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Conducting systematic, partly automated simulation studies – Unde Venis et Quo Vadis

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AIP Conference Proceedings 2020年第1期2293卷

作者： Pia Wilsdorf Fiete Haack Kai Budde Andreas Ruscheinski Adelinde M. Uhrmacher Modeling and Simulation Group Institute for Visual and Analytic Computing Department of Computer Science and Electrical Engineering University of Rostock D-18055 Rostock Germany

Simulation studies are intricate processes in which model building, model refinement, and a wide variety of simulation experiments are typically closely intertwined to achieve the objective of the simulation study. To (semi-)automatically support this process, the central artifacts of a simulation study, such as simulation models and simulation experiments, need to be made explicit and accessible. Furthermore, the relations between the artifacts as well as their context (e.g., the objectives, data sources, and requirements) have to be made explicit in an unambiguous manner. If this information is enriched by knowledge about modeling and simulation approaches or specific application domains, interpretation and reuse of the various (intermediate) artifacts and activities are facilitated even more. The resulting information can then be exploited to assist modelers in selecting and conducting the subsequent simulation experiments, which we demonstrate using a cell biological simulation study.

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Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: Evaluation in Alzheimer's disease

arXiv

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arXiv 2020年

作者： Dyrba, Martin Hanzig, Moritz Altenstein, Slawek Bader, Sebastian Ballarini, Tommaso Brosseron, Frederic Buerger, Katharina Cantré, Daniel Dechent, Peter Dobisch, Laura Düzel, Emrah Ewers, Michael Fliessbach, Klaus Glanz, Wenzel Haynes, John-Dylan Heneka, Michael T. Janowitz, Daniel Keles, Deniz B. Kilimann, Ingo Laske, Christoph Maier, Franziska Metzger, Coraline D. Munk, Matthias H. Perneczky, Robert Peters, Oliver Preis, Lukas Priller, Josef Rauchmann, Boris Roy, Nina Scheffler, Klaus Schneider, Anja Schott, Björn H. Spottke, Annika Spruth, Eike J. Weber, Marc-André Ertl-Wagner, Birgit Wagner, Michael Wiltfang, Jens Jessen, Frank Teipel, Stefan J. Rostock Germany Institute of Visual and Analytic Computing University of Rostock Rostock Germany Berlin Germany Department of Psychiatry and Psychotherapy Charité - Universitätsmedizin Berlin Campus Charité Mitte Berlin Germany Bonn Germany Department for Neurodegenerative Diseases and Geriatric Psychiatry University Hospital Bonn Bonn Germany Munich Germany University Hospital Ludwig Maximilian University Munich Germany Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology Rostock University Medical Center Rostock Germany MR-Research in Neurosciences Department of Cognitive Neurology Georg-August-University Goettingen Germany Magdeburg Germany Otto-von-Guericke University Magdeburg Germany Bernstein Center for Computational Neuroscience Berlin Germany Department of Psychiatry and Psychotherapy Charité - Universitätsmedizin Berlin Campus Benjamin Franklin Berlin Germany Department of Psychosomatic Medicine Rostock University Medical Center Rostock Germany Tuebingen Germany Section for Dementia Research Hertie Institute for Clinical Brain Research Tuebingen Germany Department of Psychiatry and Psychotherapy University of Tuebingen Tuebingen Germany Department of Psychiatry Medical Faculty University of Cologne Cologne Germany Department of Psychiatry and Psychotherapy Otto-von-Guericke University Magdeburg Germany Systems Neurophysiology Department of Biology Darmstadt University of Technology Darmstadt Germany Department of Psychiatry and Psychotherapy University Hospital Ludwig Maximilian University Munich Germany Ludwig Maximilian University Munich Germany School of Public Health Imperial College London London United Kingdom Department of Psychiatry and Psychotherapy Klinikum rechts der Isar Technical University Munich Munich Germany Department for Biomedical Magnetic Resonance University of Tuebingen Tuebingen Germany Goettingen Germany Department of Psychiatry and Psychotherapy

Background: Although convolutional neural networks (CNN) achieve high diagnostic accuracy for detecting Alzheimer's disease (AD) dementia based on magnetic resonance imaging (MRI) scans, they are not yet applied in clinical routine. One important reason for this is a lack of model comprehensibility. Recently developed visualization methods for deriving CNN relevance maps may help to fill this gap as they allow the visualization of key input image features that drive the decision of the model. We investigated whether models with higher accuracy also rely more on discriminative brain regions predefined by prior knowledge. Methods: We trained a CNN for the detection of AD in N=663 T1-weighted MRI scans of patients with dementia and amnestic mild cognitive impairment (MCI) and verified the accuracy of the models via cross-validation and in three independent samples including in total N=1655 cases. We evaluated the association of relevance scores and hippocampus volume to validate the clinical utility of this approach. To improve model comprehensibility, we implemented an interactive visualization of 3D CNN relevance maps, thereby allowing intuitive model inspection. Results: Across the three independent datasets, group separation showed high accuracy for AD dementia versus controls (AUC≥0.91) and moderate accuracy for amnestic MCI versus controls (AUC≈0.74). Relevance maps indicated that hippocampal atrophy was considered as the most informative factor for AD detection, with additional contributions from atrophy in other cortical and subcortical regions. Relevance scores within the hippocampus were highly correlated with hippocampal volumes (Pearson's r ≈ -0.86, p Copyright © 2020, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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