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Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch) Purpose: Incidental aneurysms pose a challenge to physicians who need to decide whether or not to treat them. A statistical model could potentially support such treatment decisions. The aim of this study was to compare a previously developed aneurysm rupture logistic regression probability model (LRM) to other machine learning (ML) classifiers for discrimination of aneurysm rupture status. Methods: Hemodynamic, morphological, and patient-related information of 1631 cerebral aneurysms characterized by computational fluid dynamics simulations were used to train support vector machines (SVMs) with linear and RBF kernel (RBF-SVM), k-nearest neighbors (kNN), decision tree, random forest, and multilayer perceptron (MLP) neural network classifiers for predicting the aneurysm rupture status. The classifiers’ accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were evaluated and compared to the LRM using 249 test cases obtained from two external cohorts. Additionally, important variables were determined based on the random forest and weights of the linear SVM. Results: The AUCs of the MLP, LRM, linear SVM, RBF-SVM, kNN, decision tree, and random forest were 0.83, 0.82, 0.80, 0.81, 0.76, 0.70, and 0.79, respectively. The accuracy ranged between 0.76 (decision tree,) and 0.79 (linear SVM, RBF-SVM, and MLP). Important variables for predicting the aneurysm rupture status included aneurysm location, the mean surface curvature, and maximum flow velocity. Conclusion: The performance of the LRM was overall comparable to that of the other ML classifiers, confirming its potential for aneurysm rupture assessment. To further improve the predictions, additional information, e.g., related to the aneurysm wall, might be needed.

Instruction scheduling and register allocation for VLIW architectures are complex problems for which computing the optimal solution is often infeasible. Instead, optimization techniques and heuristics are used to find good solutions in reasonable time. List scheduling is a well known microcode compaction method, which uses weights derived from data dependency graphs of the input program in its heuristic function. Additional information and mechanisms have to be used in order to reach better code compaction. In this paper, a genetic algorithm is used to tune the heuristics during list scheduling, which allows dynamic adaption of the algorithm to the given input program. The genetic scheduler often outperforms list scheduling with static heuristic and handles situations with register file pressure that might be impossible to schedule with the heuristic based list scheduling. A second genetic algorithm is proposed to perform X2 operation merging, a code optimization step exploiting special execution mode of the target hardware architecture.

International audience; Grid computing has been the subject of many large national and international IT projects. However, not all goals of these projects have been achieved. In particular, the number of users lags behind the initial forecasts laid out by proponents of grid technologies. This underachievement may have led to claims that the grid concept as a whole is on its way to being replaced by Cloud computing and various X-as-a-Service approaches. In this paper, we try to analyze the current situation and to identify promising directions for future grid development. Although there are shortcomings in current grid systems, we are convinced that the concept as a whole remains valid and can benefit from new developments, including Cloud computing. Furthermore, we strongly believe that some future applications will require the grid approach and that, as a result, further research is required in order to turn this concept into reliable, efficient and user-friendly computing platforms.

A growing number of compute and data storage jobs is performed on remote resources. In a cloud environment the customer can't be sure where a particular job is physically executed and thus cannot rely on the security and confidentiality of the remote resource. A solution for this problem is operating on encrypted functions and encrypted data. This enables a customer to generate a program that can be executed by a third party, without revealing the underlying algorithm or the processed data. This helps securing applications and data in a distributed digital ecosystem. We present a method to compute a secret program on an untrusted resource using fully homomorphic encrypted circuits. We sketch an algebraic homomorphism as a cryptographic foundation and define a sample system architecture for which we provide a software implementation. Our concept solves the problems of encrypted storage access with encrypted addresses and encrypted branching: in contrast to other approaches, like static one-pass circuit simulations, our system supports dynamic parameters and non-linear programs, that render branch-decisions at runtime and cannot be represented in a circuit with hard-wired in-circuit parameters and data. Our implementation comprises the runtime environment for an encrypted program and an assembler to generate the encrypted machine code.

Natural scientists such as physicists pioneered the sharing of computing resources, which led to the creation of the Grid. The inter domain transfer process of this technology has hitherto been an intuitive process without in depth analysis. Some difficulties facing the life science community in this transfer can be understood using the Bozeman's "Effectiveness Model of Technology Transfer". Bozeman's and classical technology transfer approaches deal with technologies which have achieved certain stability. Grid and Cloud solutions are technologies, which are still in flux. We show how Grid computing creates new difficulties in the transfer process that are not considered in Bozeman's model. We show why the success of healthgrids should be measured by the qualified scientific human capital and the opportunities created, and not primarily by the market impact. We conclude with recommendations that can help improve the adoption of Grid and Cloud solutions into the biomedical community. These results give a more concise explanation of the difficulties many life science IT projects are facing in the late funding periods, and show leveraging steps that can help overcoming the "vale of tears".

Natural scientists such as physicists pioneered the sharing of computing resources, which resulted in the Grid. The inter domain transfer process of this technology has been an intuitive process. Some difficulties facing the life science community can be understood using the Bozeman's "Effectiveness Model of Technology Transfer". Bozeman's and classical technology transfer approaches deal with technologies that have achieved certain stability. Grid and Cloud solutions are technologies that are still in flux. We illustrate how Grid computing creates new difficulties for the technology transfer process that are not considered in Bozeman's model. We show why the success of health Grids should be measured by the qualified scientific human capital and opportunities created, and not primarily by the market impact. With two examples we show how the Grid technology transfer theory corresponds to the reality. We conclude with recommendations that can help improve the adoption of Grid solutions into the biomedical community. These results give a more concise explanation of the difficulties most life science IT projects are facing in the late funding periods, and show some leveraging steps which can help to overcome the "vale of tears".

This paper gives a brief overview of three dimensional input and output devices as well as future scenarios in which these devices could be used to visualize and interact with 3-D medical data in 3-D space in a "natural way" using virtual reality tehniques in real time on a medical workstation.

Within the COMED project, medical workstations have been developed which provide computer-assisted methods for image management, 2D and 3D image visualization and processing, teleconferencing and data communication An "user-friendly" human-computer interaction has to be provided.