The deep learning experience for studying the associated cancer triads (ovarian, cervical and breast)-a pharmacogenomic approach
Keywords:
Pharmacogenomics, Octapodial Approach, Deep Learning, Siamese Net, Block Chain, Breast Cancer, Ovarian Cancer, Cervical Cancer.Abstract
The work aims at designing and implementing a deep pharmacogenomic approach and proposing a secure sharing system
of patient data. It has been found that there is a correlation between the cancer types affecting breast, ovary and cervical
regions through gene expression analysis. Common mechanisms, phenotypes, chemicals (influencing these genes) have
been identified for the major genes. Their corresponding genetic signatures were identified to study the proneness of breast
cancer patients towards ovarian cancer and cervical cancer. A deep learning tool has been developed to predict the mutation
profile from pathological images. Based on the expression levels of the corresponding genes, the type of cancer could be
identified. The designed prediction model gave an initial accuracy of 70.3 %.
