Analysis of Artificial Intelligence and Natural Language Processing Significance as Expert Systems Support for E-Health Using Pre-Train Deep Learning Models
Journal Title: Acadlore Transactions on AI and Machine Learning - Year 2022, Vol 1, Issue 2
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.
Authors and Affiliations
Pascal Muam Mah
Gait Based Person Identification Using Deep Learning Model of Generative Adversarial Network
The proliferation of digital age security tools is often attributed to the rise of visual surveillance. Since an individual's gait is highly indicative of their identity, it is becoming an increasingly popular biometric...
Human Behavior Identification Based on Graphology Using Artificial Neural Network
Handwriting reflects a person's true nature, phobias, emotional outbursts, honesty, defenses and many more characteristics. Analysis of handwriting, also known as graphology, is a science that uses the strokes and patter...
A Novel Machine Learning Approach for Optimizing Radar Warning Receiver Preprogramming
Radar warning receivers (RWRs) are critical for swiftly and accurately identifying potential threats in complex electromagnetic environments. Numerous methods have been developed over the years, with recent advances in a...
COVID-19 - Outbreak Prediction Using SIR Model
This paper deals with the trendy topic of coronavirus. The disease is causing severe damage to the entire population as well as to the nation’s economy. Machine Learning algorithms like Support Vector Machines and SIR Mo...
An End-to-End CNN Approach for Enhancing Underwater Images Using Spatial and Frequency Domain Techniques
Underwater image processing area has been a central point of interest to many people in many fields such as control of underwater vehicles, archaeology, marine biology research, etc. Underwater exploration is becoming a...