What key capability do modern AI/ML systems offer that simpler, rule-based systems might miss?

Identifying subtle, non-linear patterns and novel disease patterns

The incorporation of Artificial Intelligence (AI) and Machine Learning (ML) fundamentally enhances detection capabilities beyond what older, simpler rule-based systems can achieve. While rule-based systems rely on predefined case definitions, ML models possess the ability to analyze vast datasets and learn complex, subtle, and non-linear patterns that might not immediately appear as a standardized outbreak definition. This learning capacity allows these modern systems to become increasingly precise in flagging nascent threats and, crucially, to identify *novel* or *unexpected* disease patterns that do not fit historical outbreak molds, which is vital for emerging public health risks.