Buscar
Mostrando ítems 41-46 de 46
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 ...
Influence of disability on maternal care
(Springer, 2015)
[Abstract] The purpose of the study was to examine how women with physical disabilities perceive the influence of their disability on maternal care during the first 3 years of their child’s life, to describe the main ...
OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine
(Springer Nature, 2020-03-24)
[Abstract]
Breast cancer (BC) is the leading cause of cancer-related death among women and the most commonly diagnosed cancer worldwide. Although in recent years large-scale efforts have focused on identifying new therapeutic ...
Improvement of Epitope Prediction Using Peptide Sequence Descriptors and Machine Learning
(MDPI, 2019)
[Abstract] In this work, we improved a previous model used for the prediction of proteomes as new
B-cell epitopes in vaccine design. The predicted epitope activity of a queried peptide is based on its
sequence, a known ...
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 ...
Perturbation-Theory Machine Learning (PTML) Multilabel Model of the ChEMBL Dataset of Preclinical Assays for Antisarcoma Compounds
(American Chemical Society, 2020-10-14)
[Abstract]
Sarcomas are a group of malignant neoplasms of connective tissue with a different etiology than carcinomas. The efforts to discover new drugs with antisarcoma activity have generated large datasets of multiple ...