Summary Artificial intelligence (AI) is reshaping infectious disease diagnostics by supporting clinical decision making , optimising laboratory and clinical workflows, and enabling real-time disease surveillance. AI approaches improve pathogen detection, antimicrobial stewardship , and treatment monitoring , enhancing diagnostic accuracy , efficiency, and scalability. The role of AI in combating antimicrobial resistance is particularly significant, enabling rapid pathogen identification and personalised treatment . Despite progress over the past two decades, widespread AI adoption in infectious disease diagnostics faces challenges. In high-income countries, fragmented data ecosystems , incomplete datasets , and algorithmic bias hinder clinical integration. Meanwhile, low-income and middle-income countries contend with limited digital infrastructure, unstandardised data, and financial constraints, exacerbating disparities in diagnostic access. Further barriers include concerns ove...
Media Monitoring for Signals about Emerging Threats