An Analysis of the Effects of the COVID-19 Pandemic on Women’s Anxiety and Depression Symptoms

There have been serious side effects of the COVID-19 infection. Many women have been suffering from anxiety and sadness issues after recovering from COVID. Along with the doctor’s diagnosis and information given with the medicines, there have been many machine learning methods used in the classification and prediction of such problems. The different symptoms used in these models include socioeconomic factors that influence health, morphology, medical disorders, and several biological entities. A classification system using various machine learning models is presented in this paper for the diagnosis of patients suffering from anxiety and sadness side effects. The proposed model has been built using five well-known paradigms, namely decision trees, artificial neural networks, K nearest neighbor algorithms, support vector machines, and convolutional neural networks. The results indicate that the convolutional neural network exhibits the best results. This model can be used as an economical, quick, and secure method of diagnosis.