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System for Automatic Assessment of Alzheimer’s Disease Diagnosis Based on Deep Learning Techniques
(M D P I AG, 2019-08-21)
[Abstract] Automatic detection of Alzheimer’s disease is a very active area of research. This is due to its usefulness in starting the protocol to stop the inevitable progression of this neurodegenerative disease. This ...
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 ...
EEG Signal Processing with Separable Convolutional Neural Network for Automatic Scoring of Sleeping Stage
(Elsevier, 2020-06-01)
[Abstract]
Nowadays, among the Deep Learning works, there is a tendency to develop networks with millions of
trainable parameters. However, this tendency has two main drawbacks: overfitting and resource consumption due ...
Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications
(MDPI, 2016-08-11)
[Abstract] Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other ...
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 ...
Development of a Server for the Implementation of Data Processing Pipelines and ANN Training
(MDPI, 2021)
[Abstract] Data processing and the use of machine learning techniques make it possible to solve a wide variety of problems. The great disadvantage of using this type of technology is the enormous amount of computation ...
Convolutional Neural Networks for Sleep Stage Scoring on a Two-Channel EEG Signal
(Springer Nature, 2019-06-26)
[Abstract]
Sleeping problems have become one of the major diseases all over the world. To tackle this issue, the basic tool used by specialists is the Polysomnogram, which is a collection of different signals recorded ...
Using Machine Learning to Collect and Facilitate Remote Access to Biomedical Databases: Development of the Biomedical Database Inventory
(J M I R Publications, Inc., 2021-02-25)
[Abstract]
Background:
Currently, existing biomedical literature repositories do not commonly provide users with specific means to locate and remotely access biomedical databases.
Objective:
To address this issue, ...
A review on machine learning approaches and trends in drug discovery
(Research Network of Computational and Structural Biotechnology, 2021)
Abstract: Drug discovery aims at finding new compounds with specific chemical properties for the treatment of diseases. In the last years, the approach used in this search presents an important component in computer science ...