Search results for "LEARNING"
showing 10 items of 6669 documents
Contenidos digitales y profesores universitarios: un estudio de caso sobre usos y prácticas docentes en campus virtuales
2014
El propósito de este trabajo es conocer las prácticas promovidas por los docentes universitarios de magisterio gracias al uso de contenidos digitales en campus virtuales. En esta comunicación se exponen los resultados preliminares de la investigación. La singularidad de este estudio viene marcada por la muestra, un estudio de casos, ya que se trata de cinco docentes que desarrollan su actividad profesional en universidades presenciales y online. Los primeros resultados verifican las diferencias que existen entre las universidades presenciales y online, entre otras: en el uso de la plataforma que hacen los profesores, la existencia o no de prácticas mediadas tecnológicamente, el uso y usos d…
Accelerated T2-Weighted TSE Imaging of the Prostate Using Deep Learning Image Reconstruction: A Prospective Comparison with Standard T2-Weighted TSE …
2021
Multiparametric MRI (mpMRI) of the prostate has become the standard of care in prostate cancer evaluation. Recently, deep learning image reconstruction (DLR) methods have been introduced with promising results regarding scan acceleration. Therefore, the aim of this study was to investigate the impact of deep learning image reconstruction (DLR) in a shortened acquisition process of T2-weighted TSE imaging, regarding the image quality and diagnostic confidence, as well as PI-RADS and T2 scoring, as compared to standard T2 TSE imaging. Sixty patients undergoing 3T mpMRI for the evaluation of prostate cancer were prospectively enrolled in this institutional review board-approved study between O…
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…
Preoperative CT-Based Deep Learning Model for Predicting Risk Stratification in Patients With Gastrointestinal Stromal Tumors.
2021
ObjectiveTo develop and evaluate a deep learning model (DLM) for predicting the risk stratification of gastrointestinal stromal tumors (GISTs).MethodsPreoperative contrast-enhanced CT images of 733 patients with GISTs were retrospectively obtained from two centers between January 2011 and June 2020. The datasets were split into training (n = 241), testing (n = 104), and external validation cohorts (n = 388). A DLM for predicting the risk stratification of GISTs was developed using a convolutional neural network and evaluated in the testing and external validation cohorts. The performance of the DLM was compared with that of radiomics model by using the area under the receiver operating char…
Przegląd metod śródoperacyjnej oceny marginesów w chirurgicznym leczeniu oszczędzającym gruczoł piersiowy
2021
Breast conserving therapy is the primary treatment modality in early-stage breast cancer patients. Despite the development of methods for the intraoperative assessment of tumor margins, 20–30% of patients still require re-resection due to postoperative tumor infiltration at the surgery margins. In recent years, many methods have been developed to reduce the number of re-resections due to margin infiltration. Here we review the current methods together with several more techniques under investigation.
Novel Approaches for Glioblastoma Treatment: Focus on Tumor Heterogeneity, Treatment Resistance, and Computational Tools
2019
BACKGROUND: Glioblastoma (GBM) is a highly aggressive primary brain tumor. Currently, the suggested line of action is the surgical resection followed by radiotherapy and treatment with the adjuvant temozolomide (TMZ), a DNA alkylating agent. However, the ability of tumor cells to deeply infiltrate the surrounding tissue makes complete resection quite impossible, and in consequence, the probability of tumor recurrence is high, and the prognosis is not positive. GBM is highly heterogeneous and adapts to treatment in most individuals. Nevertheless, these mechanisms of adaption are unknown. RECENT FINDINGS: In this review, we will discuss the recent discoveries in molecular and cellular heterog…
Una propuesta sobre enseñanza de la relatividad en el bachillerato como motivación para el aprendizaje de la física
2007
Relativity is a very important part of modern physics. In this paper we analyze the teaching and learning of the theory of relativity in secondary education and we show some reasoned arguments against traditional methods to teach it. Finally, a didactic proposal for the teaching of relativity is presented; it comes as a conclusion that it is possible a suitable teaching of the principles of relative which should bring into the students a change in attitude, concepts and methodology.
On Science Museums, Science Capital, and the Public Understanding of Mathematical Modelling
2020
Students’ opportunities to learn informally (e.g. by watching documentaries, visiting museums) explain socio-economic inequities in school performances. To explore informal learning about mathematical modelling, I studied two science museums, as these are environments typically visited by middle-class families. I framed the study by using the notions science capital and the public understanding of mathematical modelling (PUMM) and explored how these are mediated in science museums. The research method entailed observations of displays, artefacts, and visitors. One science museum completely detached mathematics from its use value, whereas the other offered histories of how people used mathem…
Devenir chercheur ou enseignant chercheur : le goût pour la recherche des doctorants à l'épreuve du marché du travail
2016
Faire une thèse pour devenir chercheur ou enseignant-chercheur est souvent considéré comme un parcours difficile dont le résultat est incertain. Plus que dans d’autres pays, les diplômés de doctorat en France connaissent de fortes difficultés de stabilisation sur le marché du travail. Notre recherche s’interroge sur les raisons qui conduisent les jeunes à obtenir un doctorat puis à choisir une carrière de chercheur ou d’enseignant-chercheur et enfin, à s’y stabiliser. À partir d’une enquête du Céreq, nos résultats montrent que l’intérêt pour la recherche qu’ils ont manifesté dès le début des études supérieures et le capital social vont fortement structurer leur parcours universitaire et pro…
Educational innovation in basic and advanced cardiopulmonary resuscitation in pediatrics and neonatology in a realistic context
2018
Introducción: El profesor universitario debe transmitir las habilidades técnicas y cognitivas sobre reanimación cardiopulmonar (RCP) en Pediatría con el método más efectivo. Metodología: 17 clases prácticas de Resucitación Cardiopulmonar de 2 horas para 225 alumnos. Se impartió el 2º curso de Enfermería Pediátrica de la Universidad de Valencia. Cada clase consistió en 3 casos clínicos en los que participaron 15 estudiantes y 3 monitores. El conocimiento de los estudiantes se evaluó con prueba-repetición de 11 preguntas y la satisfacción después de la simulación (cuestionario de 20 preguntas). Resultados: la media de satisfacción de los alumnos fue de 8,62 sobre 10 puntos. La evaluación de l…