Search results for "Data type"
showing 10 items of 1183 documents
Estimation of fibre orientation from digital images
2001
In this paper, estimation of fibre orientation is studied for fibre systems observable as a blurred greyscale image. The estimation method is based on scaled variograms observed along a set of sampling lines in different directions. The parameters of the orientation distribution are obtained numerically. Simulated data are used to study the statistical properties of the method.
Active learning strategies for the deduplication of electronic patient data using classification trees.
2012
Graphical abstractDisplay Omitted Highlights? Active learning for medical record linkage is used on a large data set. ? We compare a simple active learning strategy with a more sophisticated variant. ? The active learning method of Sarawagi and Bhamidipaty (2002) 6] is extended. ? We deliver insights into the variations of the results due to random sampling in the active learning strategies. IntroductionSupervised record linkage methods often require a clerical review to gain informative training data. Active learning means to actively prompt the user to label data with special characteristics in order to minimise the review costs. We conducted an empirical evaluation to investigate whether…
Adaptive memory programing for the robust capacitated international sourcing problem
2008
The International Sourcing Problem consists of selecting a subset from an available set of potential suppliers internationally located. The selected suppliers must meet the demand for items from a set of plants, which are also located worldwide. Since the costs are affected by macroeconomic conditions in the countries where the supplier and the plant are located, the formulation considers the uncertainty associated with changes in these conditions. We formulate the robust capacitated international sourcing problem by means of a scenario-optimization approach. When dealing with uncertainty, one of the most common approaches in the literature is to formulate the problem via a set of possible …
Spatiotemporal Neurodynamics Underlying Internally and Externally Driven Temporal Prediction: A High Spatial Resolution ERP Study
2015
Abstract Temporal prediction (TP) is a flexible and dynamic cognitive ability. Depending on the internal or external nature of information exploited to generate TP, distinct cognitive and brain mechanisms are engaged with the same final goal of reducing uncertainty about the future. In this study, we investigated the specific brain mechanisms involved in internally and externally driven TP. To this end, we employed an experimental paradigm purposely designed to elicit and compare externally and internally driven TP and a combined approach based on the application of a distributed source reconstruction modeling on a high spatial resolution electrophysiological data array. Specific spatiotemp…
A finite element-based machine learning approach for modeling the mechanical behavior of the breast tissues under compression in real-time
2017
[EN] This work presents a data-driven method to simulate, in real-time, the biomechanical behavior of the breast tissues in some image-guided interventions such as biopsies or radiotherapy dose delivery as well as to speed up multimodal registration algorithms. Ten real breasts were used for this work. Their deformation due to the displacement of two compression plates was simulated off-line using the finite element (FE) method. Three machine learning models were trained with the data from those simulations. Then, they were used to predict in real-time the deformation of the breast tissues during the compression. The models were a decision tree and two tree-based ensemble methods (extremely…
Transient seizure onset network for localization of epileptogenic zone: effective connectivity and graph theory-based analyses of ECoG data in tempor…
2018
Objective: Abnormal and dynamic epileptogenic networks cause difficulties for clinical epileptologists in the localization of the seizure onset zone (SOZ) and the epileptogenic zone (EZ) in preoperative assessments of patients with refractory epilepsy. The aim of this study is to investigate the characteristics of time-varying effective connectivity networks in various non-seizure and seizure periods, and to propose a quantitative approach for accurate localization of SOZ and EZ. Methods: We used electrocorticogram recordings in the temporal lobe and hippocampus from seven patients with temporal lobe epilepsy to characterize the effective connectivity dynamics at a high temporal resolution …
Neuromuscular responses to different resistance loading protocols using pneumatic and weight stack devices
2013
The purpose of this study was to examine single repetition characteristics and acute neuromuscular responses to typical hypertrophic (HL), maximal strength (MSL), and power (PL) loadings performed with two of the most common resistance modes; pneumatic and weight stack. Acute responses were assessed by measuring maximal voluntary contraction (MVC), corresponding quadriceps-EMG and resting and superimposed twitch torques. Activation level was calculated from the twitch torques. Decreases in MVC were greater during HL and MSL than during PL. During HL, resting twitch force decreased 8% (P < 0.05) more on the weight stack than on the pneumatic device. Furthermore, loading using the weight stac…
A Graph-Grammar Approach to Represent Causal, Temporal and Other Contexts in an Oncological Patient Record
1996
AbstractThe data of a patient undergoing complex diagnostic and therapeutic procedures do not only form a simple chronology of events, but are closely related in many ways. Such data contexts include causal or temporal relationships, they express inconsistencies and revision processes, or describe patient-specific heuristics. The knowledge of data contexts supports the retrospective understanding of the medical decision-making process and is a valuable base for further treatment. Conventional data models usually neglect the problem of context knowledge, or simply use free text which is not processed by the program. In connection with the development of the knowledge-based system THEMPO (The…
Reference Standards for Software Evaluation
1990
AbstractThe field of automated ECG analysis was one of the earliest topics in Medical Informatics and may be regarded as a model both for computer-assisted medical diagnosis and for evaluating medical diagnostic programs. The CSE project has set reference standards of two kinds: In a broad sense, a standard how to perform a comprehensive evaluation study, in a narrow sense, standards as specific references for evaluating computer ECG programs. The evaluation methodology used within the CSE project is described as a basis for presentation of results which are published elsewhere in this issue.
A Novel Deep Learning Stack for APT Detection
2019
We present a novel Deep Learning (DL) stack for detecting Advanced Persistent threat (APT) attacks. This model is based on a theoretical approach where an APT is observed as a multi-vector multi-stage attack with a continuous strategic campaign. To capture these attacks, the entire network flow and particularly raw data must be used as an input for the detection process. By combining different types of tailored DL-methods, it is possible to capture certain types of anomalies and behaviour. Our method essentially breaks down a bigger problem into smaller tasks, tries to solve these sequentially and finally returns a conclusive result. This concept paper outlines, for example, the problems an…