Search results for "artificial intelligence"

Segmentation-Free Estimation of Aortic Diameters from MRI Using Deep Learning

2021

Accurate and reproducible measurements of the aortic diameters are crucial for the diagnosis of cardiovascular diseases and for therapeutic decision making. Currently, these measurements are manually performed by healthcare professionals, being time consuming, highly variable, and suffering from lack of reproducibility. In this work we propose a supervised deep-learning method for the direct estimation of aortic diameters. The approach is devised and tested over 100 magnetic resonance angiography scans without contrast agent. All data was expert-annotated at six aortic locations typically used in clinical practice. Our approach makes use of a 3D+2D convolutional neural network (CNN) that ta…

Prospective validation of a time-lapse based algorithm for embryo selection

2014

First results of PACTE group's experimental research on translation competence acquisition : the acquisition of declarative knowledge of translation

2014

Autors llistats per ordre alfabètic. Investigadora principal: A. Hurtado Albir This paper presents the first results of empirical-experimental research into the Acquisition of Translation Competence (ATC): the acquisition of declarative knowledge about translation. This study is based on our previous research about Translation Competence (TC). Some of the data collection instruments have, however, been adapted for current use. Details of our research design include type of study, universe and sample population, study variables, data collection instruments, and data analysis processes. The dependent variables were knowledge of translation; translation project; identification and solution of …

2016

The goal of this article is to present a first list of ethical concerns that may arise from research and personal use of virtual reality (VR) and related technology, and to offer concrete recommendations for minimizing those risks. Many of the recommendations call for focused research initiatives. In the first part of the article, we discuss the relevant evidence from psychology that motivates our concerns. In section 1.1, we cover some of the main results suggesting that one’s environment can influence one’s psychological states, as well as recent work on inducing illusions of embodiment. Then, in section 1.2, we go on to discuss recent evidence indicating that immersion in VR can have psy…

Machine learning in management accounting research: Literature review and pathways for the future

2021

This paper explores the possibilities of machine learning (ML) methods in management accounting research and showcases one future avenue in practice by applying ML-based textual literature review to ML/AI research in accounting. The review reveals that machine learning methods in management accounting (MA) are still in their infancy, and current research in accounting has progressed in and focused mainly on three areas related to ML and AI: 1) effects on the field of accounting and the development of the accounting profession, 2) textual analysis related to accounting data/reports, and 3) prediction methods. Based on our literature review and recently published related ML research from othe…

An experimental testbed of an Internet of Underwater Things

2020

A number of critical features have so far slowed down the realization of an Internet of Underwater Things. The most relevant of these aspects are related to the unreliability of the communication channel, the long propagation delay and the effect of severe multi-path and fading. This paper presents the design and development of a hybrid underwater-terrestrial IoT where different underwater sensors collect heterogeneous data and use marine acoustic modems to send information to a gateway device; this is able to set up a long distance link, implemented through a LoRaWAN connection, to forward data to a remote cloud for further processing. Performance of this system has been tested in a real s…

Non-cognate translation priming effects in the same–different task: evidence for the impact of “higher level” information

2015

Norris and colleagues have proposed that priming effects observed in the masked prime same–different task are based solely on pre-lexical orthographic information. This proposal was evaluated by examining translation priming effects from non-cognate translation equivalents using both Spanish–English and Japanese–English bilinguals in the same–different task. Although no priming was observed for Spanish–English bilinguals, who also produced very little translation priming in a lexical decision task, significant priming was observed for Japanese–English bilinguals. These results indicate that, although most of the priming in the same–different task has an orthographic basis, other types of pr…

Self-Organising Maps: A new way to screen the level of satisfaction of dialysis patients

2012

Highlights? FME as dialysis services global provider monitors patient satisfaction in its network. ? A specific questionnaire was developed and administered to the hemodialysis patients. ? To detect residual area of low satisfaction the Self-Organising Map was implemented. ? This method allows identifying niches of dissatisfaction for specific patient groups. Evaluation of patient satisfaction has become an important indicator for assessing health care quality. Fresenius Medical Care (FME) as a global provider of dialysis services through its NephroCare network has a strong interest in monitoring patient satisfaction.The aim of the paper is to test and validate a methodology for detecting a…

Subsequent Keyframe Generation for Visual Servoing

2021

International audience; In this paper, we study the problem of autonomous and reliable positioning of a camera w.r.t. an object when only this latter is known but not the rest of the scene. We propose to combine the advantages and efficiency of a visual servoing scheme and the generalization ability of a generative adversarial network. The paper describes how to efficiently create a synthetic dataset in order to train a network that predicts an intermediate visual keyframe between two images. Subsequent predictions are used as visual features to autonomously converge towards the desired pose even for large displacements. We show that the proposed method can be used without any prior knowled…

Comparison of Functional Network Connectivity and Granger Causality for Resting State fMRI Data

2017

Functional network connectivity (FNC) and Granger causality have been widely used to identify functional and effective connectivity for resting functional magnetic resonance imaging (fMRI) data. However, the relationship between these two approaches is still unclear, making it difficult to compare results. In this study, we investigate the relationship by constraining the FNC lags and the causality coherences for analyzing resting state fMRI data. The two techniques were applied respectively to examine the connectivity within default mode network related components extracted by group independent component analysis. The results show that FNC and Granger causality provide complementary result…