Page No: 78-92
Abstract : : Artificial Intelligence (AI) technologies are now widely used in a variety of fields to aid
with knowledge acquisition and decision-making. Health information systems, in particular, can
gain the most from AI advantages. Recently, symptoms-based illness prediction research and
manufacturing have grown in popularity in the healthcare business. Several scholars and
organisations have expressed an interest in applying contemporary computational tools to
analyse and create novel approaches for rapidly and accurately predicting illnesses. In this study,
we present a paradigm for assessing the efficacy of combining Machine Learning (ML) and
Natural Language Processing (NLP) technologies in a disease prediction system. We scraped a
disease-symptom dataset with NLP characteristics from one of the UK's most trusted National
Health Service (NHS) websites as an example. In addition, we will thoroughly examine our data
using symptom frequency, similarity, and clustering analysis. As a consequence, we can observe
that the forecast has a high efficiency rate, but there are still some challenges to work out.
Keyword Artificial Intelligent, Data Analysis, Machine Learning, Nature Language Processing,
Health Information System, Symptoms, Disease Prediction, Symptom Frequency.