A Systematic Literature Review to Evaluate the Impact of Machine Learning and Artificial Intelligence for Lung Cancer Patient in COVID-19 Pandemic Selly Anastassia Amellia Kharis (a*), Fauzan Ihza Fajar (a), Arman Haqqi Anna Zili (b)
a) Department of Mathematics, Faculty of Science and Technology, Universitas Terbuka, South Tangerang, Banten 15418, Indonesia
*selly[at]ecampus.ut.ac.id
b) Department of Mathematics, Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Indonesia, Depok 16424, Indonesia
Abstract
The COVID-19 pandemic caused by the SARS-CoV-2 virus has affected and increased the risk of individuals with chronic (comorbid) diseases including cancer. Cancer patients are considered susceptible to COVID-19 associated with the presence of an immunosuppressive state. Even though without the COVID-19 pandemic, cancer has become one of the main causes of human death in the world. With COVID-19, cancer deaths are increasing. One type of cancer that causes many deaths is lung cancer. There are many challenges and difficulties, especially in treating lung cancer during the COVID-19 period, especially for individuals who need rapid detection of lung cancer predictions. As technology develops, experts are trying to use machine learning and artificial intelligence in the treatment and detection of lung cancer. The use of machine learning and artificial intelligence can predict lung cancer either by using data in the form of microarrays, images, and so on. Limited data on COVID-19 patients with a relatively small sample, information regarding the implementation of machine learning and artificial intelligence for the treatment of COVID-19 patients with lung cancer is still limited. Therefore, it is necessary to have a systematic literature review to explain the effect of machine learning and artificial intelligence for lung cancer patients during the COVID-19 period from existing studies. This study uses a systematic literature review sourced from the search results of journals from various countries related to lung cancer and COVID-19 in Pubmed, Science Direct, Springerlink, and Google Scholar. The results show a important role of machine learning and artificial intelligence in the detection of COVID-19 in lung cancer patients.
