Infants Disease Prediction Architecture Using Artificial Neural Networks and Digital Image Processing

Abstract

Disease prediction of infants from DNA sequences remains as an open challenge in the area of bioinformatics, which deals with understanding human diseases and in identification of new molecular target for drug discovery. To provide solution, a novel prototype architecture is designed for the disease prediction of infants, based on the combination of parent DNA using Artificial Neural Networks (ANN). The proposed system integrates Micro array Technology, Digital Image Processing and Artificial Neural Networks. By applying micro array technology to the parental DNA, a gene expression image can be obtained. The extracted gene image is further characterized with the help of Digital Image processing. A neural network is trained with the mutated value which lists the probability of diseases to the infants. The proposed architecture is implemented in MATLAB. This novel system ensures that the prediction of disease for infants is possible and can be elaborated in future.