Artificial Neural Network for Treatment Recommendation and Planning in Predictive Healthcare

Abstract

Traditional healthcare systems might neglect patient-specific variations into account as they primarily rely on the experience of the doctors and constant treatment norms. A fully implementation-based ANN-driven model for treatment planning and recommendation in predictive healthcare is shown in this study. To show real-world application, the proposed work focuses on system design, dataset use, model implementation, experimental context, and performance evaluation. To bridge the gap between research and actual clinical deployment, this presentation will bring. For accurate disease prediction, recommendations for therapy, and tailored treatment planning, artificial neural networks, or ANNs, have emerged as an essential part of predictive healthcare.