Advancements in Multi-Layer Perceptron Training to Improve Classification Accuracy

Neural Networks are the popular classification tools used in Medical diagnosis for early disease detection. The performance of Neural Networks is highly depended on the training process. In the training process, the individual weights between each of the neuron are adjusted for better classification results. Many Gradient-based and Meta-heuristic training algorithms are proposed and used by the researchers to improve the training performance of Neural Network. However, there are some limitations in both Gradient-based and Meta-heuristic algorithms when there are used individually. To overcome these limitations and to improve the Multi-Layer Perceptron Network performance Hybrid algorithms are useful. In this study, a review on advancements in Multi-Layer Perceptron Network training process for the improvement of classification performance is presented

Histopathological alterations in Senegal sole, Solea Senegalensis, from a polluted Huelva estuary (SW, Spain)

As a component of a large research project to evaluate the effects of contaminants on fish health in the field, histopathological studies have been conducted to help establish causal relationship between pollutants (heavy metals and aromatic polycyclic hydrocarbons—PAHs) and histopathological responses in Senegal sole, Solea senegalensis, from an estuary of SW Spain. Heavy metals (As, Zn, Cd, Pb, Cu and Fe) and 16 PAHs (proprietary USEPA) concentrations in water, sediment and tissues (liver and gills) and histopathological alterations in S. senegalensis from three sampling sites of Ria de Huelva estuary during 2004–2006 years have been analysed. The histopathological studies revealed seasonal and spatial differences in the lesion grade of alterations observing the highest lesion grades in fish from Odiel River and autumn season. No significant differences were observed in the alterations prevalence between sampling sites, but significant differences were observed between seasons observing the highest prevalence in autumn season. However, calculated IPAT demonstrated a low–moderate impact of pollutants on health fish. Correlations between histopathological alterations and pollutants analysed were observed being heavy metals the group that presented a major number of correlations with alterations in several organs of S. senegalensis. In evaluating the general health of fish, the use of histopathological studies in recommended for making more reliable assessment of biochemical responses in fish exposed to a variety of environmental stressors. Statistical analysis using semiquantitative data on pathological lesions can help to establish correlation between cause (stressor) and effect (biomarker)