P ORTOLAN: a Model-Driven Cartography Framework

Processing large amounts of data to extract useful information is an essential task within companies. To help in this task, visualization techniques have been commonly used due to their capacity to present data in synthesized views, easier to understand and manage. However, achieving the right visualization display for a data set is a complex cartography process that involves several transformation steps to adapt the (domain) data to the (visualization) data format expected by visualization tools. To maximize the benefits of visualization we propose Portolan, a generic model-driven cartography framework that facilitates the discovery of the data to visualize, the specification of view definitions for that data and the transformations to bridge the gap with the visualization tools. Our approach has been implemented on top of the Eclipse EMF modeling framework and validated on three different use cases

ESVM Guideline on peripheral arterial disease

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Les Facteurs nutritionnels sont-ils importants dans la survenue des accidents vasculaires cérébraux ischémiques des sujets de moins de 65 ans ?

RENNES1-BU Santé (352382103) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Artériopathie des membres inférieurs athéromateuse : diagnostic [Diagnosis of lower limb peripheral artery disease]

International audienceLower limb peripheral artery disease is highly prevalent worldwide and in France. Three different stages can be found: asymptomatic stage, exercise ischemia stage, rest ischemia stage. This review based on current recommendations presents how to diagnose the different stages (Ankle brachial index, Toe-brachial index, oxymetry at rest and exercise oxymetry) in order to manage these patients

Les Facteurs nutritionnels sont-ils importants dans la survenue des accidents vasculaires cérébraux ischémiques des sujets de moins de 65 ans ?

RENNES1-BU Santé (352382103) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

The use of the tyrosine kinase inhibitor Nilotinib in Spondyloarthritis: does targeting inflammatory pathways with a treatment lead to vascular toxicity?

Abstract Spondylarthritis (SpA) is an inflammatory rheumatic disease associated with increased incidence of major adverse cardiovascular events (MACEs). Recently, Paramarta et al. proposed the use of the tyrosine kinase inhibitor Nilotinib in Spondyloarthritis to target certain inflammatory pathways. However, Nilotinib, which is highly effective for the treatment of patients with chronic myeloid leukaemia (CML), is also associated with an increased risk of MACEs. The authors suggest that Nilotinib may be effective in peripheral SpA by modulating inflammation, but not in axial SpA. Considering the vascular toxicity of Nilotinib and the acceleration of atherosclerosis in SpA patients, we suggest taking MACEs as an end-point in future trials

Use of a Pre-Trained Neural Network for Automatic Classification of Arterial Doppler Flow Waveforms: A Proof of Concept

International audienceBackground: Arterial Doppler flow waveform analysis is a tool recommended for the management of lower extremity peripheral arterial disease (PAD). To standardize the waveform analysis, classifications have been proposed. Neural networks have shown a great ability to categorize data. The aim of the present study was to use an existing neural network to evaluate the potential for categorization of arterial Doppler flow waveforms according to a commonly used classification. Methods: The Pareto efficient ResNet-101 (ResNet-101) neural network was chosen to categorize 424 images of arterial Doppler flow waveforms according to the Simplified Saint-Bonnet classification. As a reference, the inter-operator variability between two trained vascular medicine physicians was also assessed. Accuracy was expressed in percentage, and agreement was assessed using Cohen's Kappa coefficient. Results: After retraining, ResNet-101 was able to categorize waveforms with 83.7 and PLUSMN; 4.6% accuracy resulting in a kappa coefficient of 0.79 (0.75-0.83) (CI 95%), compared with a kappa coefficient of 0.83 (0.79-0.87) (CI 95%) between the two physicians. Conclusion: This study suggests that the use of transfer learning on a pre-trained neural network is feasible for the automatic classification of images of arterial Doppler flow waveforms.</p&gt

Exercise Ischemia Induced by Essential Thrombocytemia Diagnosed on Treadmill Test - Transcutaneous Oxygen Pressure Measurement of Foot Ischemia -

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