Analysis of Machine Learning Techniques for Detection of Tumor Suppressor Genes for Early Detection of Cancer: A Systematic Literature Review (original) (raw)

2021 International Conference on Innovative Computing (ICIC), 2021

Abstract

Epidemiogical evidence has shown that tumor suppressor genes early detection can play an important part in the management of cancer. The statistics at a glance for all over the world about the burden of cancer have proved that cancer is another principal reason of death across the globe and it is also responsible for the about 9.6 million deaths in a single year. It is perceived that about 1 out of 6 deaths across the globe is due to cancer and about 70% of the deaths are more likely to occur in low and middle income or developing countries because tumor suppressor genes are not detected on early stages. In this regard, a systematic meta-analysis is conducted for the observation of role imparted. In this regard, 50 research articles have been used for the observation of role of tumor suppressor genes and one of the really exciting things about the tumor suppressor genes which is excluded from the research involves the fact that through genes transplant, cancer can be cured if the abnormal functionality is detected in early stages of cancer.

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