One of the most popular domains that have caught the attention of researchers is real-time surveillance in the health and informatics segment. Many initiatives have been discovered due to this real-time surveillance surrounding public health informatics. Real-time surveillance in the health and informatics field has used the information from social media to predict the outbreak of diseases as well as to look after the diseases. There is no doubt in the fact that the availability of the data from social media in the recent past, especially the data from Twitter, has offered the researchers real-time syndromic surveillance in making quick analyses and conclusions in investigating the disease outbreak. The paper will get to know about the recent work of machine learning trends and text classification that has been utilized by the surveillance system by using the data from social media in the field of healthcare. Apart from this, the paper has also discussed the various limitations and challenges by taking into account the future direction that can be considered in this domain further.
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