Optimized artificial neural network for classification of biological data

Abstract

Biological data suffers from the problem of high dimensionality which makes the process of multi-class classification difficult and also these data have elements that are incomplete and redundant. Breast Cancer is currently one of the most pre-dominant causes of death in women around the globe. The current methods for classifying a tumour as malignant or benign involve physical procedures. This often leads to mental stress. Research has now sought to implement soft computing techniques in order to classify tumours based on the data available. In this paper, a novel classifier model is implemented using Artificial Neural Networks. Optimization is done in this neural network by using a meta-heuristic algorithm called the Whale Swarm Algorithm in order to make the classifier model accurate. Experimental results show that new technique outperforms other existing models.

Effect of Neem (Azadirachta indica ) leaves and seeds extract On the germination of six pathogenic fungi

“…Tests carried out on Azadirachta indica leaf extracts showed that they exhibit immunomodulatory, anti-inflammatory, antihyperglycaemic, antiulcer, antimalarial, antifungal, antibacterial, antioxidant, antimutagenic and anticarcinogenic properties 27 .…”