Listar GI-RNASA - Artigos por título
Mostrando ítems 37-56 de 193
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Automatic Assessment of Alzheimer’s Disease Diagnosis Based on Deep Learning Techniques
(Elsevier, 2020-05)[Abstract] Early detection is crucial to prevent the progression of Alzheimer’s disease (AD). Thus, specialists can begin preventive treatment as soon as possible. They demand fast and precise assessment in the diagnosis ... -
Automatic multiscale vascular image segmentation algorithm for coronary angiography
(Elsevier, 2018-09)[Abstract] Cardiovascular diseases, particularly severe stenosis, are the main cause of death in the western world. The primary method of diagnosis, considered to be the standard in the detection and quantification of ... -
Automatic Seizure Detection Based on Star Graph Topological Indices
(Elsevier, 2012-08-15)[Abstract] The recognition of seizures is very important for the diagnosis of patients with epilepsy. The seizure is a process of rhythmic discharge in brain and occurs rarely and unpredictably. This behavior generates a ... -
Automatic solar cell diagnosis and treatment
(Springer, 2021-04)[Abstract]: Solar cells represent one of the most important sources of clean energy in modern societies. Solar cell manufacturing is a delicate process that often introduces defects that reduce cell efficiency or compromise ... -
Avoiding the Inherent Limitations in Datasets Used for Measuring Aesthetics When Using a Machine Learning Approach
(Hindawi Limited, 2019)[Abstract]: An important topic in evolutionary art is the development of systems that can mimic the aesthetics decisions made by human begins,e.g., fitness evaluations made by humans using interactive evolution in generative ... -
BIcenter-AD: Harmonising Alzheimer’s Disease cohorts using a common ETL tool
(Elsevier, 2022)[Abstract]: Background: Many scientific studies have sought to obtain a better understanding of specific medical conditions. Concerning Alzheimer’s Disease, there is a lack of reliable diagnostics and this can be related ... -
Bio-AIMS collection of chemoinformatics web tools based on molecular graph information and artificial intelligence models
(Bentham, 2015-09-01)[Abstract] The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction ... -
Biomedical data integration in computational drug design and bioinformatics
(Bentham Science, 2013)[Abstract In recent years, in the post genomic era, more and more data is being generated by biological high throughput technologies, such as proteomics and transcriptomics. This omics data can be very useful, but the real ... -
BiOSS: A system for biomedical ontology selection
(Elsevier Ireland Ltd, 2014-04)In biomedical informatics, ontologies are considered a key technology for annotating, retrieving and sharing the huge volume of publicly available data. Due to the increasing amount, complexity and variety of existing ... -
Breast density classification to reduce false positives in CADe systems
(Elsevier, 2013)[Abstract] This paper describes a novel weighted voting tree classification scheme for breast density classification. Breast parenchymal density is an important risk factor in breast cancer. Moreover, it is known that ... -
Carbapenem Resistance in Acinetobacter nosocomialis and Acinetobacter junii Conferred by Acquisition of blaOXA-24/40 and Genetic Characterization of the Transmission Mechanism between Acinetobacter Genomic Species
(American Society for Microbiology, 2022)[Abstract] Carbapenem resistance is increasing among Gram-negative bacteria, including the genus Acinetobacter. This study aimed to characterize, for the first time, the development of carbapenem resistance in clinical ... -
Carbon nanotubes’ effect on mitochondrial oxygen flux dynamics: polarography experimental study and machine learning models using star graph trace invariants of Raman spectra
(MDPI, 2017-11-11)[Abstract] This study presents the impact of carbon nanotubes (CNTs) on mitochondrial oxygen mass flux (Jm) under three experimental conditions. New experimental results and a new methodology are reported for the first ... -
Carbon Nanotubes’ Effect on Mitochondrial Oxygen Flux Dynamics: Polarography Experimental Study and Machine Learning Models using Star Graph Trace Invariants of Raman Spectra
(M D P I AG, 2017-11-11)[Abstract] This study presents the impact of carbon nanotubes (CNTs) on mitochondrial oxygen mass flux (Jm) under three experimental conditions. New experimental results and a new methodology are reported for the first ... -
Classical Music Prediction and Composition by Means of Variational Autoencoders
(MDPI AG, 2020-04-27)[Abstract] This paper proposes a new model for music prediction based on Variational Autoencoders (VAEs). In this work, VAEs are used in a novel way to address two different issues: music representation into the latent ... -
Classification of mild cognitive impairment and Alzheimer’s Disease with machine-learning techniques using 1H Magnetic Resonance Spectroscopy data
(Elsevier, 2015-03-30)[Abstract] Several magnetic resonance techniques have been proposed as non-invasive imaging biomarkers for the evaluation of disease progression and early diagnosis of Alzheimer’s Disease (AD). This work is the first ... -
Classification of Signals by Means of Genetic Programming
(Springer, 2013-03-30)[Abstract] This paper describes a new technique for signal classification by means of Genetic Programming (GP). The novelty of this technique is that no prior knowledge of the signals is needed to extract the features. ... -
Comparativa de metodologías de desarrollo de aplicaciones móviles
(3Ciencias, 2021)[Resumen] El desarrollo de aplicaciones móviles en la actualidad tiene una gran aceptación gracias al avance de la tecnología y producción de toda clase de dispositivos que permiten a los usuarios realizar tareas ... -
Comparison of Outlier-Tolerant Models for Measuring Visual Complexity
(MDPI AG, 2020-04-24)[Abstract] Providing the visual complexity of an image in terms of impact or aesthetic preference can be of great applicability in areas such as psychology or marketing. To this end, certain areas such as Computer Vision ... -
Complex systems in aesthetics and arts
(Hindawi, 2019-05-02) -
Computational models of neuron-astrocyte interactions lead to improved efficacy in the performance of neural networks
(Hindawi, 2012)[Abstract] The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has ...