A Machine Learning-Based Model for Epidemic Forecasting and Faster Drug Discovery

Today, healthcare system models should have high accuracy and sensitivity so that patients do not have a misdiagnosis. For this reason, sufficient knowledge of the area is required, with the medical staff being able to validate the correctness of their decisions. Therefore, artificial intelligence (AI) in combination with other emerging technologies could provide many benefits in the medical sector. In this paper, we demonstrate the combination of Internet of Things (IoT) and cloud computing (CC) with AI-related techniques such as artificial intelligence (AI), machine learning (ML), deep learning (DL), and neural networks (NN) in order to provide a useful approach for scientists and doctors. Our proposed model makes use of these immersive technologies so as to provide epidemic forecasting and help accelerate drug and antibiotic discovery.

Automated summary

This paper discusses the combination of Internet of Things and cloud computing with AI, ML, DL, and NN, providing a useful approach for scientists and doctors in terms of epidemic forecasting and accelerating drug and antibiotic discovery.