Review on Sentiment Analysis of Health Related Dataset based on Machine Learning Techniques

The interpretation and categorization of sentiments and opinions from the text is known as sentiment analysis. Due to the rapid propagation of minor health-related events, it is very difficult to extract information from unorganized narratives. Despite neural network techniques' effectiveness in enhancing learning structural dependability, when using less valuable feature sets, they provide insufficient accuracy in the categorization of bio-medical sentiments. They have no discriminating potential as a result. In this study, we analyze the research areas of sentiment analysis which implements machine learning methods on the dataset from large scale patients’ narratives, social media and biomedical dataset.