Search results for "CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL"
showing 10 items of 21 documents
ReMindCare App for Early Psychosis: Pragmatic Real World Intervention and Usability Study
2020
[EN] Background: eHealth interventions are widely used in clinical trials and increasingly in care settings as well; however, their efficacy in real-world contexts remains unknown. ReMindCare is a smartphone app that has been systematically implemented in a first episode of psychosis program (FEPP) for patients with early psychosis since 2018. Objective: The objective of this study was to assess the efficacy of ReMindCare after 19 months of use in the clinic and varying use by individual patients. Methods: The integration of the ReMindCare app into the FEPP started in October 2018. Patients with early psychosis self-selected to the app (ReMindCare group) or treatment as usual (TAU group). T…
A Parallel Approach to HRTF Approximation and Interpolation Based on a Parametric Filter Model
2017
[EN] Spatial audio-rendering techniques using head-related transfer functions (HRTFs) are currently used in many different contexts such as immersive teleconferencing systems, gaming, or 3-D audio reproduction. Since all these applications usually involve real-time constraints, efficient processing structures for HRTF modeling and interpolation are necessary for providing real-time binaural audio solutions. This letter presents a parametric parallel model that allows us to perform HRTF filtering and interpolation efficiently from an input HRTF dataset. The resulting model, which is an adaptation from a recently proposed modeling technique, not only reduces the size of HRTF datasets signific…
CHAIMELEON Project: Creation of a Pan-European Repository of Health Imaging Data for the Development of AI-Powered Cancer Management Tools
2022
[EN] The CHAIMELEON project aims to set up a pan-European repository of health imaging data, tools and methodologies, with the ambition to set a standard and provide resources for future AI experimentation for cancer management. The project is a 4 year long, EU-funded project tackling some of the most ambitious research in the fields of biomedical imaging, artificial intelligence and cancer treatment, addressing the four types of cancer that currently have the highest prevalence worldwide: lung, breast, prostate and colorectal. To allow this, clinical partners and external collaborators will populate the repository with multimodality (MR, CT, PET/CT) imaging and related clinical data. Subse…
A formal model based on Game Theory for the analysis of cooperation in distributed service discovery
2016
New systems can be designed, developed, and managed as societies of agents that interact with each other by offering and providing services. These systems can be viewed as complex networks where nodes are bounded rational agents. In order to deal with complex goals, they require cooperation of the other agents to be able to locate the required services. The aim of this paper is formally and empirically analyze under which circumstances cooperation emerges in decentralized search of services. We propose a repeated game model that formalizes the interactions among agents in a search process where agents are free to choose between cooperate or not in the process. Agents make decisions based on…
A happiness degree predictor using the conceptual data structure for deep learning architectures
2017
Abstract Background and Objective: Happiness is a universal fundamental human goal. Since the emergence of Positive Psychology, a major focus in psychological research has been to study the role of certain factors in the prediction of happiness. The conventional methodologies are based on linear relationships, such as the commonly used Multivariate Linear Regression (MLR), which may suffer from the lack of representative capacity to the varied psychological features. Using Deep Neural Networks (DNN), we define a Happiness Degree Predictor (H-DP) based on the answers to five psychometric standardized questionnaires. Methods: A Data-Structure driven architecture for DNNs (D-SDNN) is proposed …
Application of a self-learning methodology for the enhancement of the oral communication student outcome in International Business studies
2019
[EN] Effective oral communication is one of the most demanded student outcomes in the labour market, especially for degree students on International Business. Although this outcome is usually evaluated in several subjects along the curriculum, it is barely worked neither inside nor outside the classroom, mainly due to lack of time and to unavailability of proper learning methodologies. The PIMECOE project, an innovation and educational improvement project on this matter, has developed a self-learning methodology on the Effective Oral Communication student outcome, in which auto-diagnosis tests, selflearning tools and peer assessments are conveniently combined to enhance the proficiency leve…
Analysis of the main weaknesses of university students regarding the "effective oral communication" student outcome
2019
[EN] The "Effective oral communication" is one of the most demanded student outcomes in the workplace, since being a good communicator is essential in any field. Inefficient communication can lead to misinterpretations and erroneous conclusions. Therefore, it is a very important student outcome both in the university and in the workplace. The student or graduate must know how to communicate effectively, both orally and in writing, appropriately using the necessary resources and adapting to the characteristics of the situation and the audience. However, despite its importance, the disparity in the mastery level of the oral communication student outcome by students makes it difficult to work …
Capability-based Communication Analysis for Enterprise Modelling
2018
Capability-oriented enterprise modelling can provide effective solutions to face changing business context. In the business domain, the notion of capability has gained a lot of attention since it guides the activities of service specification and design. Simultaneously, the research community has been promoting the integration of model-driven development (MDD) approaches with enterprise modelling to support the link between enterprise and software specifications. This integration has becoming vital to ensure the traceability of enterprise models and software implementations, acceleration of software time to market, quality assurance, and enterprise model evolution support. The capability-dr…
Multiproject–multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy
2008
[EN] Automatic brain tumor classification by MRS has been under development for more than a decade. Nonetheless, to our knowledge, there are no published evaluations of predictive models with unseen cases that are subsequently acquired in different centers. The multicenter eTUMOUR project (2004-2009), which builds upon previous expertise from the INTERPRET project (2000-2002) has allowed such an evaluation to take place. A total of 253 pairwise classifiers for glioblastoma, meningioma, metastasis, and low-grade glial diagnosis were inferred based on 211 SV short TE INTERPRET MR spectra obtained at 1.5 T (PRESS or STEAM, 20-32 ms) and automatically pre-processed. Afterwards, the classifiers …
Temporal variability analysis reveals biases in electronic health records due to hospital process reengineering interventions over seven years
2019
[EN] Objective To evaluate the effects of Process-Reengineering interventions on the Electronic Health Records (EHR) of a hospital over 7 years. Materials and methods Temporal Variability Assessment (TVA) based on probabilistic data quality assessment was applied to the historic monthly-batched admission data of Hospital La Fe Valencia, Spain from 2010 to 2016. Routine healthcare data with a complete EHR was expanded by processed variables such as the Charlson Comorbidity Index. Results Four Process-Reengineering interventions were detected by quantifiable effects on the EHR: (1) the hospital relocation in 2011 involved progressive reduction of admissions during the next four months, (2) th…