(Re)Considering Craft and Centralizing Cultures: A Revision of the Introductory Creative Writing Workshop

This article explores options for introductory creative writing curricula that allow for and encourage a greater consideration of personal identity and audience on the part of the student-author. It reaches toward possibilities for revising the introductory creative writing course as a space for student-authors to not only consider the cultural positions of the professional authors they study, but also the ways in which their own subject-positions influence their writing practices, craft choices, and understandings of genre. The article overall proposes a holistic revision to the standard, introductory creative writing curriculum, moving student-authors beyond considerations of “good” creative writing, and toward a more common consideration of cultural inclusion and diversity

In vitro and in vivo behaviour of paclitaxel loaded lipid nanocapsules

International audienc

Evolutions chimico-minéralogiques du grenat et de la muscovite au voisinage de l'isograde biotite-staurotide dans un métamorphisme prograde de type barrovien : un exemple en vendée littorale (Massif armoricain).

National audienc

Multi-expert annotation of Crohn’s disease images of the small bowel for automatic detection using a convolutional recurrent attention neural network

International audienceBackground and study aims: Computer-aided diagnostic tools using deep neural networks are efficient for detection of lesions in endoscopy but require a huge number of images. The impact of the quality of annotation has not been tested yet. Here we describe a multi-expert annotated dataset of images extracted from capsules from Crohn’s disease patients and the impact of the quality of annotations on the accuracy of a recurrent attention neural network.Methods: Images of capsule were annotated by a reader first and then reviewed by three experts in inflammatory bowel disease. Concordance analysis between experts was evaluated by Fleiss’ kappa and all the discordant images were, again, read by all the endoscopists to obtain a consensus annotation. A recurrent attention neural network developed for the study was tested before and after the consensus annotation. Available neural networks (ResNet and VGGNet) were also tested under the same conditions.Results: The final dataset included 3498 images with 2124 non-pathological (60.7 %), 1360 pathological (38.9 %), and 14 (0.4 %) inconclusive. Agreement of the experts was good for distinguishing pathological and non-pathological images with a kappa of 0.79 (P < 0.0001). The accuracy of our classifier and the available neural networks increased after the consensus annotation with a precision of 93.7 %, sensitivity of 93 %, and specificity of 95 %.Conclusions: The accuracy of the neural network increased with improved annotations, suggesting that the number of images needed for the development of these systems could be diminished using a well-designed dataset