Combining Genetic Algorithms and SVM for Breast Cancer Diagnosis Using Infrared Thermography.

Journal: Sensors (Basel, Switzerland)
Published Date: Jul 14, 2021

Abstract

Breast cancer is one of the leading causes of mortality globally, but early diagnosis and treatment can increase the cancer survival rate. In this context, thermography is a suitable approach to help early diagnosis due to the temperature difference between cancerous tissues and healthy neighboring tissues. This work proposes an ensemble method for selecting models and features by combining a Genetic Algorithm (GA) and the Support Vector Machine (SVM) classifier to diagnose breast cancer. Our evaluation demonstrates that the approach presents a significant contribution to the early diagnosis of breast cancer, presenting results with 94.79% Area Under the Receiver Operating Characteristic Curve and 97.18% of Accuracy.

Authors

  • Roger Resmini
    Institute of Exact and Natural Sciences, Federal University of Rondonópolis, Cidade Universitária, Rondonópolis 78736-900, MT, Brazil.
  • Lincoln Silva
    Visual Lab, Institute of Computing, Fluminense Federal University, Av. Gal. Milton Tavares de Souza, S/N, Niterói 24210-346, RJ, Brazil.
  • Adriel S Araujo
    Visual Lab, Institute of Computing, Fluminense Federal University, Av. Gal. Milton Tavares de Souza, S/N, Niterói 24210-346, RJ, Brazil.
  • Petrucio Medeiros
    Mídiacom Lab, Institute of Computing, Fluminense Federal University, R. Passo da Pátria 156, Niterói 24210-240, RJ, Brazil.
  • Débora Muchaluat-Saade
    Mídiacom Lab, Institute of Computing, Fluminense Federal University, R. Passo da Pátria 156, Niterói 24210-240, RJ, Brazil.
  • Aura Conci
    Computing Institute, Federal Fluminense University, Niterói, Rio de Janeiro, Brazil.

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