Explainable artificial intelligence and machine learning: novel approaches to face infectious diseases challenges

Artificial intelligence (AI) and machine learning (ML) are revolutionizing human activities in various fields, with medicine and infectious diseases being not exempt from their rapid and exponential growth. Furthermore, the field of explainable AI and ML has gained particular relevance and is attracting increasing interest. Infectious diseases have already started to benefit from explainable AI/ML models. For example, they have been employed or proposed to better understand complex models aimed at improving the diagnosis and management of coronavirus disease 2019, in the field of antimicrobial resistance prediction and in quantum vaccine algorithms. Although some issues concerning the dichotomy between explainability and interpretability still require careful attention, an in-depth understanding of how complex AI/ML models arrive at their predictions or recommendations is becoming increasingly essential to properly face the growing challenges of infectious diseases in the present century.KEY MESSAGES center dot AI and ML are revolutionizing human activities in various fields, and infectious diseases are not exempt from their rapid and exponential growth.center dot Despite some notable challenges, explainable AI/ML could provide insights into the decision-making process, making the outcomes of models more transparent.center dot Improved transparency can help to build trust among healthcare professionals, policymakers, and the general public in leveraging AI/ML-based systems to face the growing challenges of infectious diseases in the present century.