Social media based surveillance systems for healthcare using machine learning: A systematic review
The inclusion of online data in surveillance systems has improved the disease prediction ability over traditional syndromic surveillance systems, however, social media based surveillance systems have many limitations and challenges, including noise, demographic bias, privacy issues, etc.
Abstract
The inclusion of online data in surveillance systems has improved the disease prediction ability over traditional syndromic surveillance systems. However, social media based surveillance systems have many limitations and challenges, including noise, demographic bias, privacy issues, etc. Our paper mentions future directions, which can be useful for researchers working in the area. Researchers can use this paper as a library for social media based surveillance systems in the healthcare domain and can expand such systems by incorporating the future works discussed in our paper.