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Comparison of Bayesian approaches for develo** prediction models in rare disease: application to the identification of patients with Maturity-Onset Diabetes of the Young
BackgroundClinical prediction models can help identify high-risk patients and facilitate timely interventions. However, develo** such models for...
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Multipath feature recalibration DenseNet for image classification
Recently, deep neural networks have demonstrated their efficiency in image classification tasks, which are commonly achieved by an extended depth and...
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LSVT-BIG therapy in Parkinson’s disease: physiological evidence for proprioceptive recalibration
BackgroundThere is growing evidence for proprioceptive dysfunction in patients with Parkinson’s disease (PD). The Lee Silvermann Voice Treatment-BIG...
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Changes in body perception following virtual object manipulation are accompanied by changes of the internal reference scale
Changes in body perception often arise when observers are confronted with related yet discrepant multisensory signals. Some of these effects are...
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Salient Object Detection with Edge Recalibration
Salient Object Detection (SOD) based on Convolutional Neural Networks (CNNs) has been widely studied recently. How to maintain a complete and clear...
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The Recalibration of Force in International Counterterrorism, 2010–2020
In 2014 David Cameron declared that IS presented an existential threat to the vital interests of Britain and lobbied hard to persuade Parliament to...
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Salient object detection based on adaptive recalibration technique through deep network
Object detection is most required task in computer vision to meet the requirement of autonomous processes. The key challenge in object detection is...
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Data synchronization techniques and their impact on the prediction performance of automated recalibrated soft sensors in bioprocesses
Innovative soft sensor concepts can recalibrate automatically when the prediction performance decreases due to variations in raw materials,...
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Parametric and Multivariate Uncertainty Calibration for Regression and Object Detection
Reliable spatial uncertainty evaluation of object detection models is of special interest and has been subject of recent work. In this work, we...
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Adaptation of risk prediction equations for cardiovascular outcomes among patients with type 2 diabetes in real-world settings: a cross-institutional study using common data model approach
ObjectiveTo adapt risk prediction equations for myocardial infarction (MI), stroke, and heart failure (HF) among patients with type 2 diabetes in...
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Repeatedly experiencing the McGurk effect induces long-lasting changes in auditory speech perception
In the McGurk effect, presentation of incongruent auditory and visual speech evokes a fusion percept different than either component modality. We...
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Enactive planning in rock climbing: recalibration, visualization and nested affordances
This paper analyzes the skilled performance of rock climbing through the framework of Embodied and Enacted Cognitive Science. It introduces a notion...
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Temporal adaptation of sensory attenuation for self-touch
The sensory consequences of our actions appear attenuated to us. This effect has been reported for external sensations that are evoked by auditory or...
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Recalibration and validation of the Swiss lichen bioindication methods for air quality assessment
The aim of this study was to recalibrate the Swiss lichen bioindication methods, developed and calibrated with air pollution data 30 years ago. Since...
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Development of IoT-Healthcare Model for Gastric Cancer from Pathological Images
The diagnosis of stomach cancer automatically in digital pathology images is a difficult problem. Gastric cancer (GC) detection and pathological...
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Image Super-Resolution via Deep Feature Recalibration Network
Recent years have witnessed remarkable progress in convolutional neural network (CNN) based image super-solution (SR) methods. Existing methods tend...
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Response shift results of quantitative research using patient-reported outcome measures: a descriptive systematic review
PurposeThe objective of this systematic review was to describe the prevalence and magnitude of response shift effects, for different response shift...
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Cardinal v.3: a versatile open-source software for mass spectrometry imaging analysis
Cardinal v.3 is an open-source software for reproducible analysis of mass spectrometry imaging experiments. A major update from its previous...
