BACKGROUND Artificial neural networks is one of pattern analyzer method which are rapidly applied on a bio-medical field. OBJECTIVE The aim of this research was to propose an appendicitis diagnosis system using artificial neural networks (ANNs). METHODS Data from 801 patients of the university hospital in Dongguk were used to construct artificial neural networks for diagnosing appendicitis ...

Cryptography is the ability of changing information into obvious unintelligibility in a way allowing a secret method of un-mangling. The vital idea of cryptography is the capability to send information between participants in a way that prevents others from reading it. Much cryptography methods are available which are based on number theory but it has the disadvantage of requirement a large com...

This paper presents a computer-based decision support system for automated interpretation of diagnostic heart images (called WeAidU), which is made available via the Internet. The system is based on image processing techniques, artificial neural networks (ANNs) and large well-validated medical databases. We present results using artificial neural networks, and compare with two other classificat...

Industrial pollution is often considered to be one of the prime factors contributing to air, water and soil pollution. Sectoral pollution loads (ton/yr) into different media (i.e. air, water and land) in Lagos were estimated using Industrial Pollution Projected System (IPPS). These were further studied using Artificial neural Networks (ANNs), a data mining technique that has the ability of dete...

Artificial Neural Networks (ANNs) attempt to mimic human neural networks in order to perform tasks. In order to do this, tasks need to be represented in ways that the network understands. In ANNs these representations are often arbitrary, whereas in humans it seems that these representations are often meaningful. This article shows how using more meaningful representations in ANNs can be very b...

Artificial Neural Networks (ANNs) have been used to perform classification for Automatic Speech Recognition (ASR). In this paper, we propose a new neural network, the Contenders' Network (CN) which requires little initial knowledge of the classification problem and lesser neurons than other ANNS

This paper presents an overview on applications of artificial neural network in electric power industry (EPI) which is currently undergoing an extraordinary development. One of the most thrilling and potentially cost-effective recent developments in this field is increasing usage of artificial intelligence techniques viz. artificial neural networks (ANNs), genetic algorithm, fuzzy logic, and ex...

Pyrolysis-mass spectrometry and artificial neural networks (ANNs) were used in combination to provide quantitative analyses of mixtures of casamino acids in glycogen, as representatives of complex proteins and carbohydrates. We studied fully interconnected feedforward networks, whose weights were modified using various types of back-propagation algorithms, and which exploited a sigmoidal activa...

In this paper the performance of Artificial Neural Networks (ANNs) and Adaptive Neuro- Fuzzy Inference Systems (ANFIS) in simulating the inverse dynamic behavior of Magneto- Rheological (MR) dampers is investigated. MR dampers are one of the most applicable methods in semi active control of seismic response of structures. Various mathematical models are introduced to simulate the dynamic behavi...

The forecast of fluctuations and prices is the major concern in financial markets. Thus, developing an accurate and robust forecasting decision model is critically favorable to the investors. As gold has shown a special capability to smooth inflation fluctuations, governors use gold as a price controlling lever. Thus, more information about future gold price trends will help to make the firm de...