Enhanced Healthcare Intelligence for Vaccination Prediction and Recommendation Using Deep Swarm Feature Engineering with Hyper Capsule Generated Adversarial Neural Network

Abstract

In recent years we have witnessed significant growth of healthcare protocols through vaccines to safeguard individuals from diseases without side effects. Especially various diseases that affect people's lead series effects caused by COVID-19, H1N1, Flu type of viruses. Vaccination protects us before it affects us to defend ourselves. Identifying all over-vaccination apart from other immunity-less people's prediction is challenging for early identification and recommendation. Most traditional methods failed to analyze active threshold margins' feature dimension and mutual dependencies, leading to a higher false negative and degrading prediction accuracy. The active false rate reduces the precision and recall accuracy and increases the false rate. To resolve this problem, we propose an enhanced deep feature engineering based on swarm intelligence whale optimization algorithm (SIWOA) with Hyper Capsule Generated Adversarial Neural Network (HCGANN) for vaccination prediction and recommendation. Initially, the Min-max normalizer is applied to preprocess the patient data, including patient information and vaccination details. The vaccination impact rate (VIR) is estimated using the scalar decision algorithm to calculate the absolute feature limits. Then, the Swarm Intelligence Whale Optimization Algorithm (SIWOA) is applied to select the essential features to reduce the non-mutual feature weights. The Generated adversarial neural network takes ideal feature limits of mutual dependencies of correlation vector to predict the vaccination recommendation people depend on a class by category. The proposed system improves the active false optimistic rate prediction by effectively evaluating the vaccination impact on people to improve prediction accuracies. The increased precision, recall rate, and f1 measure project higher evaluation results than the other systems.