Search results for " classification"
showing 10 items of 1043 documents
Trends in Radical Prostatectomy Risk Group Distribution in a European Multicenter Analysis of 28 572 Patients: Towards Tailored Treatment
2019
Background: Active surveillance (AS) has been increasingly proposed as the preferential initial management strategy for low-risk prostate cancer (PC), while in high-risk PC the indication for surgery has widened. Objective: To evaluate the development of risk group distribution of patients undergoing radical prostatectomy (RP). Design, setting, and participants: Retrospective database review of combined RP databases (2000-2015) of four large European centers (Créteil, Paris; San Rafaele, Milan; Martini Klinik, Hamburg; NKI, AvL, Amsterdam). Outcome measurements and statistical analysis: Clinical and pathological characteristics per year of surgery. Eligibility for AS was defined according …
Diagnostic accuracy of computed tomographic colonography for the detection of advanced neoplasia in individuals at increased risk of colorectal cance…
2009
CONTEXT: Computed tomographic (CT) colonography has been recognized as an alternative for colorectal cancer (CRC) screening in average-risk individuals, but less information is available on its performance in individuals at increased risk of CRC. OBJECTIVE: To assess the accuracy of CT colonography in detecting advanced colorectal neoplasia in asymptomatic individuals at increased risk of CRC using unblinded colonoscopy as the reference standard. DESIGN, SETTING, AND PARTICIPANTS: This was a multicenter, cross-sectional study. Individuals at increased risk of CRC due to either family history of advanced neoplasia in first-degree relatives, personal history of colorectal adenomas, or positiv…
Between context and comparability: Exploring new solutions for a familiar methodological challenge in qualitative comparative research
2020
Finding the balance between adequately describing the uniqueness of the context of studied phenomena and maintaining sufficient common ground for comparability and analytical generalisation has widely been recognised as a key challenge in international comparative research. Methodological reflections on how to adequately cover context and comparability have extensively been discussed for quantitative survey or secondary data research. In addition, most recently, promising methodological considerations for qualitative comparative research have been suggested in comparative fields related to higher education. The article’s aim is to connect this discussion to comparative higher education rese…
Convolutional Neural Networks for Multispectral Image Cloud Masking
2020
Convolutional neural networks (CNN) have proven to be state of the art methods for many image classification tasks and their use is rapidly increasing in remote sensing problems. One of their major strengths is that, when enough data is available, CNN perform an end-to-end learning without the need of custom feature extraction methods. In this work, we study the use of different CNN architectures for cloud masking of Proba-V multispectral images. We compare such methods with the more classical machine learning approach based on feature extraction plus supervised classification. Experimental results suggest that CNN are a promising alternative for solving cloud masking problems.
On central algorithms of approximation under fuzzy information
2005
We consider the problem of approximation of an operator by information described by n real characteristics in the case when this information is fuzzy. We develop the well-known idea of an optimal error method of approximation for this case. It is a method whose error is the infimum of the errors of all methods for a given problem characterized by fuzzy numbers in this case. We generalize the concept of central algorithms, which are always optimal error algorithms and in the crisp case are useful both in practice and in theory. In order to do this we define the centre of an L-fuzzy subset of a normed space. The introduced concepts allow us to describe optimal methods of approximation for lin…
Fuzzy expected utility
1984
Decision making under uncertainty requires not only measures of the uncertainty of situations that we try to recognize , but also an estimate of the imprecision from which they are determined. This imprecision can be the result either of a lack of exactness in the measure of the elements which are necessary to the determination of the states of nature or the purely subjective interpretation of these states. Through a subjective measure of the non-measurable imprecision, the purpose of the fuzzy expected utility, which is investigated, is to translate with a great accuracy the imprecise behaviour of the decision-maker in an uncertain world. Consequently we propose to introduce first the prob…
The fuzzy p-median problem
2004
In many location models, the strong crisp assumptions, like known demands and distances, are not realistic in most cases. The fuzzy p-median problem relaxes this hypothesis giving to the decision maker a necessary degree of freedom to solve real-world problems. It allows a decision maker to improve an optimal covering of a location problem by considering partially feasible solutions in which some demand is left uncovered. Here we revise the main facts and results about this problem emphasising different specific algorithms of resolution. Finally we show that this fuzzy version can be used to analyse the global structure of a given instance of the crisp problem.
Soft-computing based heuristics for location on networks: The p-median problem
2011
We propose a genetic algorithm for the fuzzy p-median problem in which the optimal transport cost of the associated crisp problem is unknown. Our algorithm works with two populations: in one, the solutions with a better crisp transport cost are favored by the selection criterion, whereas in the second one, solutions with a better fuzzy satisfaction level are preferred. These populations are not independent. On the contrary, the first one periodically invades the second one, thus providing new starting points for finding fuzzy improvements. Our computational results also reveal the importance of choosing adequate functions for selecting the parents. Our best results are obtained with functio…
Involving fuzzy orders for multi-objective linear programming
2012
This paper presents a solution approach for multi-objective linear programming problem. We propose to involve fuzzy order relations to describe the objective functions where in ”classical” fuzzy approach the membership functions which illustrate how far the concrete point is from the solution of individual problem are studied. Further the global fuzzy order relation is constructed by aggregating the individual fuzzy order relations. Thus the global fuzzy relation contains the information about all objective functions and in the last step we find a maximum in the set of constrains with respect to the global fuzzy order relation. We illustrate this approach by an example.
Controller Design Under Fuzzy Pole-Placement Specifications: An Interval Arithmetic Approach
2006
This paper discusses fuzzy specifications for robust controller design, as a way to define different specification levels for different plants in a family and allow the control of performance degradation. Controller synthesis will be understood as mapping a fuzzy plant onto a desired fuzzy set of closed-loop specifications. In this context, a fuzzy plant is considered as a possibility distribution on a given plant space. In particular, pole placement in linear plants with fuzzy parametric uncertainty is discussed, although the basic idea is general and could be applied to other settings. In the case under consideration, the controller coefficients are the solution of a fuzzy linear system o…