Search results for " learning"
showing 10 items of 5299 documents
Deep Neural Networks for Prediction of Exacerbations of Patients with Chronic Obstructive Pulmonary Disease
2018
Chronic Obstructive Pulmonary Disease (COPD) patients need help in daily life situations as they are burdened with frequent risks of acute exacerbation and loss of control. An automated monitoring system could lead to timely treatments and avoid unnecessary hospital (re-)admissions and home visits by doctors or nurses. Therefore we present a Deep Artificial Neural Networks for approach prediction of exacerbations, particularly Feed-Forward Neural Networks (FFNN) for classification of COPD patients category and Long Short-Term Memory (LSTM), for early prediction of COPD exacerbations and subsequent triage. The FFNN and LSTM models are trained on data collected from remote monitoring of 94 pa…
The effect of social information from live demonstrators compared to video playback on blue tit foraging decisions.
2019
Video playback provides a promising method to study social interactions, and the number of video playback experiments has been growing in recent years. Using videos has advantages over live individuals as it increases the repeatability of demonstrations, and enables researchers to manipulate the features of the presented stimulus. How observers respond to video playback might, however, differ among species, and the efficacy of video playback should be validated by investigating if individuals’ responses to videos are comparable to their responses to live demonstrators. Here, we use a novel foraging task to compare blue tits’ (Cyanistes caeruleus) responses to social information from a live …
Nessuno resta indietro: La Bellezza del Service Learning
2021
La chiusura delle scuole che ha provocato un incremento significativo della povertà educativa ha sollecitato l’opportunità di pro-gettare interventi integrati di service learning per favorire il recupero e il potenziamento dei minori in difficoltà. 869 studenti del Corso di Laurea Magistrale in Scienze della Formazione Primaria dell’Università degli Studi di Palermo, sono stati coinvolti nella progettazione e nella realizzazione di percorsi didattici mirati, rivolti agli alunni “fragili” di 33 scuole palermitane. Complessiva-mente sono state erogate 60.000 ore in DAD di attività di recupero e di potenziamento dell’apprendimento di alunni della scuola primaria di Palermo. Le attività didatti…
Special issue BOOK OF ABSTRACT 2022 CTRAS CONFERENCE NEW AND OLD CHALLENGES TO SUPPORT ALL STUDENTS’ MATHEMATICS TEACHING AND LEARNING IN INCLUSIVE, …
2022
Special issue BOOK OF ABSTRACT 2022 CTRAS CONFERENCE
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…