In 1998, over 400 papers on artificial neural networks (ANNs) were published in the context of medicine, but why is there this interest in ANNs? And how do ANNs compare with traditional statistical methods? We propose some answers to these questions, and go on to consider the ‘black box’ issue. Finally, we briefly look at two directions in which ANNs are likely to develop, namely the use of Bayesian statistics and knowledge data fusion
Artificial neural networks (ANNs) are relatively new computational tools that have been extensively ...
cOMMentArY Artificial neural networks (ANNs) are a class of powerful machine learning models for cl...
Artificial neural networks (ANN) are designed to simulate the behavior of biological neural networks...
The long course of evolution has given the human brain many desirable characteristics not present in...
Throughout the years, the computational changes have brought growth to new technologies.Such is the ...
The latest and most interesting development in the field of Deep Learning (DL) is an artificial neur...
There are numerous applications of Artificial Neural Networks (ANN) at the present time and there ar...
Artificial neural networks are 'biologically' inspired networks.They have the ability to learn from ...
The human brain contains around 86 billion nerve cells and about as many glial cells [1]. In additio...
Introduction: Artificial neural networks mimic brains behavior. They are able to predict and feature...
Artificial Neural Networks or widely known as Neural networks (ANNs or NNs) is a computational parad...
This thesis describes research conducted at City University into the application of Artificial Neura...
Artificial Neural Networks (ANN) are currently exploited in many scientific domains. They had shown...
An Artificial Neural Network (ANN) is a data processing paradigm inspired by the way biologica...
Artificial Neural Networks (ANN) are currently exploited in many scientific domains. They had shown ...
Artificial neural networks (ANNs) are relatively new computational tools that have been extensively ...
cOMMentArY Artificial neural networks (ANNs) are a class of powerful machine learning models for cl...
Artificial neural networks (ANN) are designed to simulate the behavior of biological neural networks...
The long course of evolution has given the human brain many desirable characteristics not present in...
Throughout the years, the computational changes have brought growth to new technologies.Such is the ...
The latest and most interesting development in the field of Deep Learning (DL) is an artificial neur...
There are numerous applications of Artificial Neural Networks (ANN) at the present time and there ar...
Artificial neural networks are 'biologically' inspired networks.They have the ability to learn from ...
The human brain contains around 86 billion nerve cells and about as many glial cells [1]. In additio...
Introduction: Artificial neural networks mimic brains behavior. They are able to predict and feature...
Artificial Neural Networks or widely known as Neural networks (ANNs or NNs) is a computational parad...
This thesis describes research conducted at City University into the application of Artificial Neura...
Artificial Neural Networks (ANN) are currently exploited in many scientific domains. They had shown...
An Artificial Neural Network (ANN) is a data processing paradigm inspired by the way biologica...
Artificial Neural Networks (ANN) are currently exploited in many scientific domains. They had shown ...
Artificial neural networks (ANNs) are relatively new computational tools that have been extensively ...
cOMMentArY Artificial neural networks (ANNs) are a class of powerful machine learning models for cl...
Artificial neural networks (ANN) are designed to simulate the behavior of biological neural networks...