Fuzzy graphoidal covering of fuzzy graphs and its application in cancer classification under artificial neural network context

Abstract

The classification of cancers concerning their
nature and identification of the variant are very crucial
things in health sciences as decision-making. The chance
and nature of cancer in the human body are efficiently
tackled by the signaling pathways. Also, these concepts
are very vital for the up and down criteria of several
types of oncogenes. There are uncertainties in the data
of oncogene parameters and many ambiguities in the
pathways concept. We have tied these two issues in one
frame to overcome the vague sense of classification in
this work.