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Embedded System to Support Skin Cancer Recognition

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 12254)

Abstract

Skin cancer is the most common among all cancers and its early diagnosis increases the patient’s chances of healing. One of the ways to make this diagnosis is through dermatoscopy. Dermatoscopy is a technique that consists of recognizing structures present in the skin, not visible to the naked eye. Therefore, for assisting the use of dermatoscopy by health professionals, this work presents a device to support skin cancer recognition using the histogram of oriented gradients and machine learning, based on the ABCDE rule.

Keywords

  • Machine learning
  • Skin cancer
  • Histogram of Oriented Gradients
  • Gaussian Naive Bayes
  • K Neighbors Classifier

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  • DOI: 10.1007/978-3-030-58817-5_52
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Acknowledgements

This research is sponsored by the Portugal Incentive System for Research and Technological Development PEst-UID/CEC/00319/2020 and University Paulista – Software Engineering Research Group by Brazil.

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de A. Batista, G., Nogueira, M., Santos, N., Machado, R.J. (2020). Embedded System to Support Skin Cancer Recognition. In: , et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12254. Springer, Cham. https://doi.org/10.1007/978-3-030-58817-5_52

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  • DOI: https://doi.org/10.1007/978-3-030-58817-5_52

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58816-8

  • Online ISBN: 978-3-030-58817-5

  • eBook Packages: Computer ScienceComputer Science (R0)