ARTIFICIAL WEB-BASE NETWORK

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CHAPTER ONE

INTRODUCTION

1.0   GENERAL OVERVIEW

One of the motor applications of medical information has been the implantation and use of expert systems to predict medical diagnosis based upon a set of symptoms. Furthermore, such expert systems serve as aid to laboratory testing routines and effective treatments.

An intelligent computer programs assisting medical diagnosis offers the physician easy access to a wealth of information from patient’s past data. Such resources may help hospitals reduces excessive costs from unnecessary laboratory testing and ineffective patient treatment, while maintaining high quality of medical care.

The use of expert systems as means of predicting medial diagrams and recommending successful has been a highly active research filed in due past few years.

Given this point, the development of a knowledge base using this Artificial network technology naturally lend itself toward the task of predicting medical diagnosis. In addition, this technology appear to the promising method for recommendation possibly routines.

The research will construct a web-based network capable of predicting various medical diagnoses with a plausible degree of accuracy.

This expert can then be used to provide projections given new situations of interest and answer “what if” questions.

1.1   BACKGROUND OF STUDY

The history of medical diagnosis can be divided into several periods.

The first group (IBM) maintained closed contact with neuroscientists at Mc Gill University. So whenever their models did not work they consulted the neuroscientists. This interaction established a multidisciplinary trend which continues to the present day.

Promising and EmergingTechnology: – Not only was neuroscience influential in the development of networks, but psychologists and engineers also contributed to the progress of neural network simulations. In 1958 Rosenblatt Stirred considerable interest and activity in the field when the designed and developed the perception.

Another system was the ADALINE (Adaline Liner Element), which was developed in 1960 by Window Hoff (of Stanford University). The ADALINE was analogue electronic device made from simple components. 

Innovation:- Although public interest an available foundering were minimal, several researchers continued working to develop neuromophically based computational methods for problems such pattern recognition. During this period, several paradigms were generated which modern work continues to enhance. Steve Grossbery in 1980 founded a school of thoughts, which explores resonating algorithms. He and coail carpenter developed the ART (Adapline Resonance Theory) network based on biologically plausible models.

Amari Shun-Ichi in 1967 was involved with theoretical developments. He published a paper, which established a mathematical theory for a learning basis (error-correction method) dealing with adapline pattern classification. The original network was published in 1975 and was called the cognition.

Today:- Significant progress has been made in three field of neural network enough to attract a great deal of attention and funnel further re-search. Advancement beyond current commercial application appears to be possible and research in advancing the fields on many front neutrally based clips are emerging and applications to complex problems developing clearly network technology.

1.2   STATEMENT OF PROBLEM

The major problem in training a web-based network to patient diagnosis is to process the data in such a manner as could be interpreted by the neural networks variable transformation modules.

The steps toward achieving this will involve using a software package that will suit such task, this application will help the physician every patient. Problem facing manual system or conventional system in hospitals are:

Insecurity of Data:- Hospitals where manual system in operation, data are not very secured due to the way patient file are being kept in the hospitals.

Lack of file organization:– Using manual or conventional system of file/cards organizations is hospitals causes a tedious problem to the nurse/physician during storing processing and searching of past patients files. Manual system does not permit file keeping for a very longtime.

Tedious and Stressful:– Manual operating hospitals find jobs stressful and time consuming around them.

Illegibility in Writing:– Illegible writing sometimes causes time wasting while searching for patients for. Hence, these works will art against those negative vises.

1.3   OBJECTIVE OF THE RESEARCH

The objectives of this work are to design and develop a medical diagnosis system to carry out the day to day transaction of the hospital and administration. Let us take a look at the computer and manually diagnosis, computer has being in a way it helps to check and carryout medical treatment easily or better than the manually processes.

This project research is to assist physician facilitate reasonable task, treatment and minimize unnecessary laboratory routines so as to reduce operational cost, to predict medical diagnosis and possible treatment, to construct and train Artificial intelligence web-based network (AWBN) that will serve as dynamic “look up table” for accurate classification of medical diagnosis due to patient symptoms.