A Comprehensive Review of Algorithms Developed for Rapid Pathogen Detection and Surveillance

The chapter discusses the importance of early detection and surveillance of infectious diseases, including the recent COVID-19 pandemic and the threat of antimicrobial resistance. It provides a comprehensive review of current advances in AI applications for pathogen identification, antimicrobial resistance monitoring, and the discovery of novel antimicrobial therapeutics. The section on AI in pathogen identification and characterization discusses various methods, including traditional techniques and AI/ML algorithms. AI tools for early detection of infection and diagnosis was largely developed in response to COVID19 pandemic and lead the way for advanced ML/DL models for drug repurposing, novel antibiotics discovery and antimicrobial stewardship. Further, this chapter discusses the use of AI in data sharing and collaboration e.g. sharing gene sequences and utilizing federated learning as an emerging approach that addresses data sharing and privacy concerns by allowing multiple institutions to collaborate and collectively train the model. Predictive analytics where AI has been used to analyze large amounts of data to identify trends, relationships, and patterns that can be used to forecast future behavior are also covered. During pandemic, AI was used for contact tracing and social distancing as well as for public awareness and communications highlighting the ethical use of AI. Lastly, the availability of generative AI chatbots and how it can be used in infectious diseases surveillance is discussed.