Impact of covid-19 in lung cancer detection using image processing techniques, artificial intelligence and machine learning approaches

Abstract

ABSTRACT Due to their impaired immune systems, lung cancer (LC) patients are especially sensitive to COVID-19 and are more susceptible to it as well as its related effects. The diagnosis, treatment and aftercare of LC patients are exceedingly difficult and time-consuming throughout an epidemic due to a multitude of factors. In these situations, the care of LC patients using cutting-edge technologies offers the potential to enhance the diagnosis, treatment, and advancements using machine learning (ML) algorithms and artificial intelligence (AI). The researchers might be able to differentiate between lung problems brought on by the corona virus and those brought on by, for example, chemotherapy and radiation, using therapeutic and imaging data as well as ML techniques. AI ensures that the appropriate individuals are enrolled in LC clinical research more effectively and rapidly than in the past, when it was done in a conventional and time-consuming manner. To effectively treat cancer patients and find new, more potent treatments, it is critical to move past traditional research approaches and make use of artificial intelligence and machine learning (AIML). When applied to various patient populations, AI based algorithms can swiftly identify lung cancer CT scans with COVID-19-linked pneumonia and accurately distinguish non-COVID connected pneumonia, which is significant for thoughtful mechanisms of an outbreak that is significant to AI. It is possible to use the present challenges and projected futures in this study to direct the best application of AI and ML in an epidemic. GRAPHICAL ABSTRACT