Search results for " classification"

Epidemiology and surveillance of human (neuro)cysticercosis in Europe: is enhanced surveillance required?

2020

To report on relevant national surveillance systems of (N)CC and taeniasis (the infection with the adult tapeworm) in the European Union/European Economic Area and to assess the magnitude of (N)CC occurrence by retrieving information on cases for the period 2000-2016.(N)CC cases were retrieved via national reporting systems, a systematic literature search, contact with clinicians and a search for relevant 'International Statistical Classification of Diseases and Related Health Problems' (ICD)-based data.Mandatory notification systems for (N)CC were found in Hungary, Iceland and Poland. Ten cases were reported in Poland and none in Hungary and Iceland. Through the systematic literature revie…

Stronger proprioceptive BOLD-responses in the somatosensory cortices reflect worse sensorimotor function in adolescents with and without cerebral pal…

2020

Graphical abstract

Wearable electromyography recordings during daily life activities in children with cerebral palsy.

2020

To test whether wearable textile electromyography (EMG) recording systems may detect differences in muscle activity levels during daily activities between children with cerebral palsy (CP) and age-matched typically developing children.Wearable textile EMG recording systems were used to obtain leg muscle activity in 10 children with spastic CP (four females, six males; mean age 9y 6mo, standard deviation [SD] 2y 4mo, range: 6-13y; Gross Motor Function Classification System [GMFCS] level I and II) and 11 typically developing children (four females, seven males; mean age 9y 9mo, SD 1y 11mo, 7-12y) at rest and while performing seven daily activities.Children with CP showed significantly lower a…

Improved limit on the directly measured antiproton lifetime

2017

Continuous monitoring of a cloud of antiprotons stored in a Penning trap for 405 days enables us to set an improved limit on the directly measured antiproton lifetime. From our measurements we extract a storage time of $3.15\times {10}^{8}$ equivalent antiproton-seconds, resulting in a lower lifetime limit of ${\tau }_{\bar{{\rm{p}}}}\gt 10.2\,{\rm{a}}$ with a confidence level of $68 \% $. This result improves the limit on charge-parity-time violation in antiproton decays based on direct observation by a factor of 7.

Impact of changing forest management on soil organic matter in low mountain acid media

2002

The impacts of changes in vegetation cover from native deciduous forest to Douglas fir ( Pseudotsuga menziesii Franco) and of human activity on soil organic matter (SOM) characteristics were studied in two low mountain areas of east-central France. No striking difference in soil type (Dystric Cambisol) was found between the two sites. Humus-rich horizons were of the “Dysmull” and “Moder” types, regardless of the nature of the bedrock. Contrary to a common affirmation concerning other coniferous species, Douglas fir had no negative effect on soil pH and humification degree of SOM, with respect to the native beech vegetation. Pruning and partial clearing slightly improved humification, espect…

SuperHistopath: A Deep Learning Pipeline for Mapping Tumor Heterogeneity on Low-Resolution Whole-Slide Digital Histopathology Images.

2021

High computational cost associated with digital pathology image analysis approaches is a challenge towards their translation in routine pathology clinic. Here, we propose a computationally efficient framework (SuperHistopath), designed to map global context features reflecting the rich tumor morphological heterogeneity. SuperHistopath efficiently combines i) a segmentation approach using the linear iterative clustering (SLIC) superpixels algorithm applied directly on the whole-slide images at low resolution (5x magnification) to adhere to region boundaries and form homogeneous spatial units at tissue-level, followed by ii) classification of superpixels using a convolution neural network (CN…

2020

The disease and treatment of patients with head and neck cancer can lead to multiple late and long-term sequelae. Especially pain, psychosocial problems, and voice issues can have a high impact on patients’ health-related quality of life. The aim was to show the feasibility of implementing an electronic Patient-Reported Outcome Measure (PROM) in patients with head and neck cancer (HNC). Driven by our department’s intention to assess Patient-Reported Outcomes (PRO) based on the International Classification of Functioning during tumor aftercare, the program “OncoFunction” has been implemented and continuously refined in everyday practice. The new version of “OncoFunction” was evaluated by 20 …

Effectiveness of local feature selection in ensemble learning for prediction of antimicrobial resistance

2008

In the real world concepts are often not stable but change over time. A typical example of this in the biomedical context is antibiotic resistance, where pathogen sensitivity may change over time as pathogen strains develop resistance to antibiotics that were previously effective. This problem, known as concept drift (CD), complicates the task of learning a robust model. Different ensemble learning (EL) approaches (that instead of learning a single classifier try to learn and maintain a set of classifiers over time) have been shown to perform reasonably well in the presence of concept drift. In this paper we study how much local feature selection (FS) can improve ensemble performance for da…

Modeling Multi-label Recurrence in Data Streams

2019

Most of the existing data stream algorithms assume a single label as the target variable. However, in many applications, each observation is assigned to several labels with latent dependencies among them, which their target function may change over time. Classification of such non-stationary multi-label streaming data with the consideration of dependencies among labels and potential drifts is a challenging task. The few existing studies mostly cope with drifts implicitly, and all learn models on the original label space, which requires a lot of time and memory. None of them consider recurrent drifts in multi-label streams and particularly drifts and recurrences visible in a latent label spa…

Drug Activity Characterization Using One-Class Support Vector Machines with Counterexamples

2013

The problem of detecting chemical activity in drugs from its molecular description constitutes a challenging and hard learning task. The corresponding prediction problem can be tackled either as a binary classification problem (active versus inactive compounds) or as a one class problem. The first option leads usually to better prediction results when measured over small and fixed databases while the second could potentially lead to a much better characterization of the active class which could be more important in more realistic settings. In this paper, a comparison of these two options is presented when support vector models are used as predictors.