Impetuous development of artificial neural networks makes it possible to transfer many ideas from this area into adjacent areas. This work investigates an opportunity of mapping learning classifier systems (LCS) into artificial neural networks (ANN). Possible learning types for hybrid connectionist classifier system (CLCS) for multi-step problems are derived. Transformation’s opportunity of the...

Lung cancer is the leading cancer among both men and women. A quality preprocessing technique is necessary to ensure effective removal of noise that interferes with the features of the image and hence improves lung cancer detection rate and accuracy. In this proposed research, we will extract basic Geometric Features from Lang DICOM as well as JPEG image Format and Based on Random Forest Classi...

As the use of searching digital images has increased a lot in recent years, so a system is required which search images from large database on the bases of query image and return results in form of images which matched with query image. The present paper introduces a content based image retrieval system using artificial neural network (ANN) approach as soft computing technique. The proposed sys...

Speech processing has emerged as one of the important application area of digital signal processing. Various fields for research in speech processing are speech recognition, speaker recognition, speech synthesis, speech coding etc. Speaker recognition is one of the most useful and popular biometric recognition techniques in the world especially related to areas in which security is a major conc...

In this study, a biomedical diagnosis system for pattern recognition with normal and abnormal classes has been developed. First, feature extraction processing was made by using the Doppler Ultrasound. During feature extraction stage, Wavelet transforms and shorttime Fourier transform were used. As next step, wavelet entropy were applied to these features. In the classification stage, hidden Mar...

One fourth of the world population is affected by mental disorders during their lives. Due to lack of distinct etiology, classification of such mental disorder is based on signs and symptoms and is vulnerable to errors. In this paper, an Artificial Neural Network (ANN) classifier is proposed that is trained using past classification data so that it can correctly classify new patients based on t...

Specific gene expression regulation strategy using antisense oligonucleotides occupy significant space in recent clinical trials. The therapeutical potential of oligos lies in the identification and prediction of accurate oligonucleotides against specific target mRNA. In this work we present a computational method that is built on Artificial Neural Network (ANN) which could recognize and predic...

PURPOSE The paper presents a complete computer-aided detection (CAD) system for the detection of lung nodules in computed tomography images. A new mixed feature selection and classification methodology is applied for the first time on a difficult medical image analysis problem. METHODS The CAD system was trained and tested on images from the publicly available Lung Image Database Consortium (...