Abstract:
Machine learning is a field of artificial intelligence that allows computer systems to learn from their experiences rather than having to be designed for every eventuality. The dataset considered in this paper is the Covid dataset. Early detection of covid-19 symptoms, including diabetes, is crucial since it minimizes the risk of mortality from the condition. This effort makes systematic attempts to develop a system that may predict diseases like diabetes as well as symptoms that lead to covid. As a result, one of the most critical medical issues is detecting symptoms of covid-19 at an early stage. Covid-Database studies have been completed. A comparison of machine learning prognostication accuracy classifiers with dataset can also be found here. With this data, it's obvious that the model improves diagnostic accuracy and consistency by employing a range of methods, as well as other covid symptoms. The developed framework, which incorporates various machine learning classifiers, can be used to predict or identify other diseases in the future. The study may be broadened and strengthened to make symptoms of covid-19 analysis easier, by including many additional machine learning approaches.
