Neural networks : the official journal of the International Neural Network Society
May 14, 2021
We introduce the novel concept of anti-transfer learning for speech processing with convolutional neural networks. While transfer learning assumes that the learning process for a target task will benefit from re-using representations learned for anot...
Interdisciplinary sciences, computational life sciences
May 14, 2021
Cardiovascular Disease (CVD) is one among the main factors for the increase in mortality rate worldwide. The analysis and prediction of this disease is yet a highly formidable task in medical data analysis. Recent advancements in technology such as B...
Electrocardiogram (ECG) is a commonly-used, non-invasive examination recording cardiac voltage versus time traces over a period. Deep learning technology, a robust artificial intelligence algorithm, can imitate the data processing patterns of the hum...
Increases in the scale and complexity of behavioral data pose an increasing challenge for data analysis. A common strategy involves replacing entire behaviors with small numbers of handpicked, domain-specific features, but this approach suffers from ...
BACKGROUND: Machine learning sustains successful application to many diagnostic and prognostic problems in computational histopathology. Yet, few efforts have been made to model gene expression from histopathology. This study proposes a methodology w...
Electroencephalography (EEG) microstate analysis is a method wherein spontaneous EEG activity is segmented at sub-second levels to analyze quasi-stable states. In particular, four archetype microstates and their features are known to reflect changes ...
Introducing a knowledge graph into a recommender system as auxiliary information can effectively solve the sparse and cold start problems existing in traditional recommender systems. In recent years, many researchers have performed related work. A re...
The prediction of relative humidity is a challenging task because of its nonlinear nature. The machine learning-based prediction strategies have attained significant attention in tackling a broad class of challenging nonlinear and complex problems. T...
No comprehensive review of Bayesian networks (BNs) in healthcare has been published in the past, making it difficult to organize the research contributions in the present and identify challenges and neglected areas that need to be addressed in the fu...
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