Use of Artificial Intelligence (AI): A Developing Assessment Techniques for Study of Tumor Diversity from Gene Expression

Abstract

Cancer is one of the commonly occurring diseases in the human that causes the greatest number of deaths globally per year. Usually, the classification of tumor diversity has been based on the consensus of study of the signs of the disease using the microscopic examination, with very limited consideration of molecular pathology. Tissue helps us to decide the prognostic and predictive aspects of breast cancer. Tumor and clinical multiformity are one of the key causes of the letdown of proper medical treatment. The Classification of tumor multiformity using evolving tools definitely improves prognosis and later helps to propose proper treatment plans. AI is one of the evolving methods for classifying the heterogeneous data available, including diverse risk factors. Moreover, the application of AI seems one of the effective tools for the analysis of raw feature data for all the genes cancer. In this article, we review the distinct AI techniques for grouping of data and extraction of key features