Principles of medical diagnostics of malignant human skin cancer using artificial neural networks.

Keywords: artificial neural network, innovations, mechanism, diagnostics, medicine, skin diseases, malignant tumor, oncology, automation.

Abstract

The principles of medical diagnostics of human skin cancer using artificial neural networks are presented. Aspects of the development of artificial intelligence that allow creating intelligent systems based on biological approaches in various fields of application are disclosed. The stages of oncological diagnostics are characterized, which are mandatory and have a fundamental impact on the further treatment of the patient in the case of diagnosis of malignant skin cancer, the result of each of the stages is a clinical diagnosis, morphological diagnosis and pathologic diagnosis. The concept of melanoma and its development features are outlined. The algorithms of automated computer analysis of dermatological images that provide assistance to doctors in making a diagnosis and contribute to improving the accuracy of diagnostics are studied. A block diagram for diagnosing human skin cancer using artificial neural networks has been developed. The problem of differentiation of human skin pathologies is based on a conditional division into 4 parts for solving binary classification problems. It is emphasized that the artificial neural network is trained using data sets. It is noted that given the problems of binary classification, in each direction of application, data sets are assigned labels of class zero and one, represented as an array. In the article, a detailed algorithm described in the form of a flowchart is developed that is able to make a final medical diagnosis of skin diseases and oncological pathologies using an artificial neural network. The described algorithm is based on artificial neural networks trained to solve binary classification problems. The result of the artificial neural network is the output of the membership of the input value of classes that describe the neural network passed the training stage.

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Published
2020-09-19
How to Cite
Zahorodnii, O. (2020). Principles of medical diagnostics of malignant human skin cancer using artificial neural networks . COMPUTER-INTEGRATED TECHNOLOGIES: EDUCATION, SCIENCE, PRODUCTION, (40), 31-36. https://doi.org/10.36910/6775-2524-0560-2020-40-05