Pigmented Dermatological Lesions Classification Using Convolutional Neural Networks Ensemble Mediated By Multilayer Perceptron Network

Authors

  • Carlos Maurício Seródio Figueiredo

Keywords:

Artificial Intelligence, Deep Learning, Clinical Images Classification, Pigmented Dermatological Lesions

Abstract

This paper presents the development of a Deep Learning model, trained from the Skin Cancer Mnist database (HAM10000). It is able to perform Classification of Pigmented Dermatological Lesions using Convolutional Neural Networks techniques by proposing an ensemble with Multilayer Perceptron Neural Networks. In order to evaluate the Convolutional Networks, the metrics Accuracy, Precision, Revocation and F1-Score were taken into consideration. The ensemble implementation was based on a Grid Search with Cross Validation and evaluated according to Accuracy. The obtained results show the relevance of the research and the consolidation of the techniques used in the development of Artificial Intelligence solutions applied in to analysis of clinical images. Accuracy, Recall and F1-Score reached 0.93 and Precision 0.94, which is superior performance to specialists and related researches.

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Published

2019-12-17

How to Cite

Figueiredo, C. M. S. (2019). Pigmented Dermatological Lesions Classification Using Convolutional Neural Networks Ensemble Mediated By Multilayer Perceptron Network. IEEE Latin America Transactions, 17(11), 1902–1908. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/1948