Antonio Soriano Payá

Review: Application of artificial neural networks in the diagnosis of urological dysfunctions

In this article, we evaluate the work out of some artificial neural network models as tools for support in the medical diagnosis of urological dysfunctions. We develop two types of unsupervised and one supervised neural network. This scheme is meant to help the urologists in obtaining a diagnosis for complex multi-variable diseases and to reduce painful and costly medical treatments since neurological dysfunctions are difficult to diagnose. The clinical study has been carried out using medical registers of patients with urological dysfunctions. The proposal is able to distinguish and classify between ill and healthy patients.

A robust model of the neuronal regulator of the lower urinary tract based on artificial neural networks

The neuronal regulator of the lower urinary tract is a very complex nervous system that consists of a heterogeneous group of neuronal centres. We have developed a new system from a model based in a multi-agent system in which each neuronal centre corresponds with an agent. This system incorporates a heuristic in order to make it more robust in the presence of possible inconsistencies. The heuristic used is based on a neural network (orthogonal associative memory). Knowledge through training has been added to the system, using correct patterns of behaviour of the urinary tract and behaviour patterns resulting from dysfunctions in two neuronal centres as a minimum. The experiments prove that the model is robust and its functioning coincides with the behaviour of the biological system. This work fulfils the expectations of providing a model of the regulator system that allows breaking the problem into simple modules each with its own entity.

Review Article: Modelling of urological dysfunctions with neurological etiology by means of their centres involved

Urinary incontinence is a considerable problem which is clearly reflected in the number of patients affected by it. Moreover, it is extremely difficult to obtain an accurate diagnosis as the urinary incontinence very often is related to the neurological system. In this article a model with capabilities for urological diagnosing is proposed. This model is specialized towards the diagnosis of urological dysfunctions with neurological etiology. For this reason the model explores all the neural centres involved in both the urological phases, voiding and micturition. Once these centres have been studied it becomes possible to establish a direct relation between neural centres which present an anomalous functioning and neurological dysfunctions.

Development of an artificial neural network for helping to diagnose diseases in urology

In this article we propose the development of a tool for helping in the medical diagnosis using neural networks, in particular the multilayer perceptron. This new tool is meant to help the urologists in obtaining an automatic diagnosis for complex multi-variable systems, and to avoid painful and costly medical treatments. The clinical study has been carried out using the medical registers of patients with dysfunctions in the lower urinary tract. The system is able to distinguish and classify dysfunctions as arreflexive, hyper-reflexive, and effort incontinence. Moreover, it is able to predict whether there is presence of dysfunction or not. The results of the experiments display a high percentage of certainty of about 85%

Modeling the Distributed Control of the Lower Urinary Tract Using a Multiagent System

In this article a model of the biological neuronal regulator system of the lower urinary tract is presented. The design and the implementation of the model has been carried out using distributed artificial intelligence, more specifically a system based on agents that carry out tasks of perception, deliberation and execution. The biological regulator is formed by neuronal centres. In the model, each agent is modeled so that its behaviour is similar to that of a neuronal centre. The use of the agent paradigm in the model confers it important properties: adaptability, distributed computing, modularity, synchronous or asynchronous functioning. This strategy also allows a complex systems approach formed by connected elements whose interaction is partially well-known. We have simulated and tested the model comparing results with clinical studies.

Mathematical modelling of the lower urinary tract

The lower urinary tract is one of the most complex biological systems of the human body as it involved hydrodynamic properties of urine and muscle. Moreover, its complexity is increased to be managed by voluntary and involuntary neural systems. In this paper, a mathematical model of the lower urinary tract it is proposed as a preliminary study to better understand its functioning. Furthermore, another goal of that mathematical model proposal is to provide a basis for developing artificial control systems. Lower urinary tract is comprised of two interacting systems: the mechanical system and the neural regulator. The latter has the function of controlling the mechanical system to perform the voiding process. The results of the tests reproduce experimental data with high degree of accuracy. Also, these results indicate that simulations not only with healthy patients but also of patients with dysfunctions with neurological etiology present urodynamic curves very similar to those obtained in clinical studies.

Modelling of dysfunctions in the neuronal control of the lower urinary tract

In this article a model of the regulator system of the lower urinary tract is presented discussing, in particular, the dysfunctions associated with the neurogenic bladder. The design and implementation of the model has been carried out using distributed artificial intelligence, more specifically a multi-agent system. Each agent is modelled so that its behaviour is similar to that of a neuronal centre. By means of this design, the behaviour of the neuronal regulator of the lower urinary tract is simulated using a model with a similar structure to the organisation of the biological system, conferring on it emergent properties. We compare the results obtained using the model in situations with several neurological dysfunctions with experimental results obtained from patients suffering from the analysed dysfunctions. The data, obtained using the model, are consistent with the existing real clinic studies in medicine related to the same dysfunctions.

An Agent Based Framework for Modelling Neuronal Regulators of the Biological Systems

The neuronal regulators of biological systems are very difficult to deal with since they present nonstructured problems. The agent paradigm can analyze this type of systems in a simple way. In this paper, a formal agent-based framework that incorporates aspects such as modularity, flexibility and scalability is presented. Moreover, it enables the modeling of systems that present distribution and emergence characteristics. The proposed framework provides a definition of a model for the neuronal regulator of the lower urinary tract. Several examples of the experiment have been carried out using the model as presented, and the results have been validated by comparing them with real data. The developed simulator can be used by specialists in research tasks, in hospitals and in the field of education.

Decision support system for the diagnosis of urological dysfunctions based on fuzzy logic

In this article a fuzzy system with capabilities for urological diagnosing is proposed. This system is specialized towards the diagnosis of urological dysfunctions with neurological etiology. For this reason the system specifies all the neural centres involved in both the urological phases, voiding and micturition. The fuzzy system allows to classify every dysfunction of all patients by means of their membership functions. The results of the experiments show that the fuzzy approach allows the diagnosis of urological dysfunctions from the relationship between neural centres and their associated neurological dysfunction.

Simulation of the Neuronal Regulator of the Lower Urinary Tract using a Multiagent System

In this paper, a model of the neuronal regulator of the lower urinary tract that regulates the micturition process is presented. A multiagent system has been used in which each agent models the behaviour of the different neuronal centres involved in the process. This model enables the distribution and emergence characteristics of neuronal regulation to be represented. Likewise, aspects such as modularity and flexibility that allow new advances in research into the nervous system to be incorporated into the model have also been taken into account. Based on the proposed model, a tool has been implemented which allows to simulate the functioning of the model showing the values related to urodymanic variables graphically. Several examples of the tests carried out with the model are presented in this paper and the results have been validated by comparing them with real data.