Abstract
Melanoma is one of the more frequently encountered cancers, which quite often depends on exposure to ultraviolet radiation occurring in solar radiation. Of course, an additional factor is individual immunity and genetics. It is important to discover the possible spread of the cancer, which in this case depends on the observation of the skin, and above all the marks. The quickest possible detection of neoplastic changes can result in a chance to prolong life. In the era of mobility, where everyone has a camera built into the phone and access to the Internet, it is possible to analyze signs by an application that would analyze the skin. In the case of detected exceptions, the application would exchange information with a publicly available database and consult with a dermatologist about the possible need for urgent hispatological examination. In this paper, we propose a model of such a system based on intelligent things along with a detailed description of individual components. As a classification component, a convolutional classifier was proposed, which accepts not only image data, but also numerical one. The analysis of the proposed solution has been tested and discussed due to numerous advantages and disadvantages of such a solution nowadays.
| Original language | English |
|---|---|
| Article number | 8868149 |
| Pages (from-to) | 149355-149363 |
| Number of pages | 9 |
| Journal | IEEE Access |
| Volume | 7 |
| DOIs | |
| Publication status | Published - 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Feature extraction
- Internet of Things
- deep learning
- image processing
ASJC Scopus subject areas
- General Computer Science
- General Materials Science
- General Engineering
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