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.
Highlights
Skin melanoma is a malignant tumor that develops via pigmented cells
The factors for melanoma development are primarily UV radiation, which occurs in solar radiation [1], [2]
At the moment, receiving immunotherapy is dependent on meeting a huge number of criteria, as well as the attending physician
Summary
Skin melanoma is a malignant tumor that develops via pigmented cells. The factors for melanoma development are primarily UV radiation, which occurs in solar radiation [1], [2]. The second motif may trim to excessive or even obsessive checking of birthmarks, which may cause us not to notice changes due to getting used to the current state With such a large amount of technology that is present in our lives, it is worth using it to control and analyze birthmarks. RELATED WORKS From a technical point of view, the best thing would be to take a picture of a particular mole, and the program returned interesting information It is quite a difficult task, because the program should know how to search, what to look for, as well as remove unwanted elements in the image. A data set consisting of a graphic file and data in numerical form are interpreted as one input for such a classifier This approach is to improve the classification process by increasing incoming data from various medical devices. The results were discussed due to comparisons with existing solutions. 5) The last section summarizes the achieved results
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