Performance analysis of melanoma classifier using electrical modeling technique.

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.Graphical abstract An equivalent electrical model is developed for designing melanoma classifier. Initially, each amino acid is modeled using the RC passive circuit depending on their physicochemical structure and hydropathy nature, to form a gene structure model. The melanoma-related genes are detected by phase, transient, and color code analysis.

journal_name

Med Biol Eng Comput

authors

Roy T,Bhattacharjee P

doi

10.1007/s11517-020-02241-6

subject

Has Abstract

pub_date

2020-10-01 00:00:00

pages

2443-2454

issue

10

eissn

0140-0118

issn

1741-0444

pii

10.1007/s11517-020-02241-6

journal_volume

58

pub_type

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