Abstract
An efficient and novel modeling approach is proposed in this paper for identifying proteins or genes involved in melanoma skin cancer. Two types of classifiers are modeled, based on the chemical structure and hydropathy property of amino acids. These classifiers are further implemented using NI LabVIEW–based hardware kit to observe the real-time response for proper diagnosis. The phase responses, pole-zero diagrams, and transient responses are examined to screen out the genes related to melanoma from healthy genes. The performance of the proposed classifier is measured using various performance measurement metrics in terms of accuracy, sensitivity, specificity, etc. The classifier is experimented along with a color code scheme on skin genes and illustrates the superiority in comparison with traditional methods by achieving 94% of classification accuracy with 96% of sensitivity.
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The working facility is provided by the University of Engineering and Management, Kolkata-700156.
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The authors would like to thank DST, Science and Engineering Research Board (EEQ/2017/000293), Govt. of India, for funding the research work.
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Roy, T., Bhattacharjee, P. Performance analysis of melanoma classifier using electrical modeling technique. Med Biol Eng Comput 58, 2443–2454 (2020). https://doi.org/10.1007/s11517-020-02241-6
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DOI: https://doi.org/10.1007/s11517-020-02241-6