Outbreak Predictions in Healthcare Domain using Machine learning & Artificial Intelligence

Abstract

AI-based technologies and machine learning are being put to use in monitoring and predicting epidemics around the world. Today, scientists have access to an outsized amount of knowledge collected from satellites, real-time social media updates, website information, etc. Artificial neural networks help to collate this information and predict every disease from various techniques & outbreaks to severe chronic infectious diseases. Predicting these outbreaks is particularly helpful in third-world countries as they lack in crucial medical infrastructure and academic systems. A primary example of this is often the ProMED-mail, an internet-based reporting platform which monitors evolving diseases and emerging ones and provides outbreak reports in real-time.
Keywords: Outbreaks, healthcare, predictions, Datasets, Behavioral Modifications, KNN Algorithm, Decision Tree, Naïve Bayes.