Automated Deep Learning based Disease Prediction Using Skin Health Records: Issues, Challenges and Future Directions

Abstract

Due to recent breakthroughs in Artificial Intelligence (AI) and automation in the healthcare industry, people have been able to see an increased possibility for merging deep learning with healthcare. Automated deep learning and healthcare integration have been found as a feasible technique for enhancing disease prediction accuracy, which will aid in disease prevention and control. AI-enabled skin health data could be used as a unique technique for preliminary body health prediction by matching symptoms and influenced skin photos to a pool of current disease databases. The goal of this research is to offer an automated deep learning framework for predicting illness outcomes based on changes in skin characteristics. Various issues and challenges are also investigated, with the purpose of anticipating the integration of deep learning into healthcare in future medical research.