In its first part, this contribution reviews shortly the application of neural network methods to medical problems and characterizes its advantages and problems in the context of the medical background. Successful application examples show that human diagnostic capabilities are significantly worse than the neural diagnostic systems. Then, paradigm of neural networks is shortly introduced and the main problems of medical data base and the basic approaches for training and testing a network by medical data are described. Additionally, the problem of interfacing the network and its result is given and the neuro-fuzzy approach is presented. Finally, as case study of neural rule based diagnosis septic shock diagnosis is described, on one hand by...
This paper presents a technique for building expert systems that combines the fuzzy-set approach wit...
Neural networks are increasingly being seen as an addition to the statistics toolkit which should be...
AbstractApplying neural networks, genetic and immune algorithms enable solving tasks of computed-aid...
The proposal of this research line is the search for alternatives to the resolution of complex probl...
In intensive care units physicians are aware of a high lethality rate of septic shock patients. In t...
In this paper, application of artificial neural networks in typical disease diagnosis has been inves...
Artificial Neural Networks or in short, Neural networks (ANNs or NNs) is a computational paradigm th...
In contrast to the symbolic approach, neural networks seldom are designed to explain what they have ...
Neural networks have been widely used in general classification tasks. They have the advantages of b...
Artificial Neural Networks or widely known as Neural networks (ANNs or NNs) is a computational parad...
Artificial intelligence applications in medicine is the major and evolutionary topic in the technolo...
The paper describes experiments with a neural network selection that works as a conclusion-making un...
Artificial Neural Networks or widely known as Neural networks (ANNs or NNs) is a computational parad...
Abstract- People these days are technically advanced and computers are widely available. People are ...
In this paper, attempt has been made to make use of Artificial Neural network in Disease Diagnosis w...
This paper presents a technique for building expert systems that combines the fuzzy-set approach wit...
Neural networks are increasingly being seen as an addition to the statistics toolkit which should be...
AbstractApplying neural networks, genetic and immune algorithms enable solving tasks of computed-aid...
The proposal of this research line is the search for alternatives to the resolution of complex probl...
In intensive care units physicians are aware of a high lethality rate of septic shock patients. In t...
In this paper, application of artificial neural networks in typical disease diagnosis has been inves...
Artificial Neural Networks or in short, Neural networks (ANNs or NNs) is a computational paradigm th...
In contrast to the symbolic approach, neural networks seldom are designed to explain what they have ...
Neural networks have been widely used in general classification tasks. They have the advantages of b...
Artificial Neural Networks or widely known as Neural networks (ANNs or NNs) is a computational parad...
Artificial intelligence applications in medicine is the major and evolutionary topic in the technolo...
The paper describes experiments with a neural network selection that works as a conclusion-making un...
Artificial Neural Networks or widely known as Neural networks (ANNs or NNs) is a computational parad...
Abstract- People these days are technically advanced and computers are widely available. People are ...
In this paper, attempt has been made to make use of Artificial Neural network in Disease Diagnosis w...
This paper presents a technique for building expert systems that combines the fuzzy-set approach wit...
Neural networks are increasingly being seen as an addition to the statistics toolkit which should be...
AbstractApplying neural networks, genetic and immune algorithms enable solving tasks of computed-aid...