Analysis of Artificial Intelligence and Natural Language Processing Significance as Expert Systems Support for E-Health Using Pre-Train Deep Learning Models

Abstract

Artificial intelligence (AI) and natural language processing (NLP) are relentless technologies for healthcare that can support a strong and secure digital system with embedded applications of internet of things (IoTs). The study tried to build an artificial intelligence-natural language processing cluster system. In the system, rich content is extracted using parts of speech and then classified into an understandable dataset. The unavailable uniqueness systems with standardize process and procedures for artificial intelligence and natural language processing across different systems to support E-healthcare sector is a big challenge for nations and the world at large. Aim to train a cluster system that extract rich content and fit into a deep learning model frame to enable interpretation of the dataset for healthcare needs through a fast and secure digital system. The study uses (behavior-oriented driven and influential functions) to determine the significance of AI and NLP on E-health. Based on a selective scorings method, a rate of 1 out of 5 grading was developed called the Key Benefits score. The behavior-oriented drive and influential function allows an in-depth evaluation of E-health based on the selection of text content applied to the sample proposed study. Results show a score of 3.947 scale significance of NLP and AI on E-health. The study concluded that well-defined artificial intelligence and natural language processing applications are perfect areas that advance positive results in healthcare electronic services.