The Role of Microbiological Monitoring in Ensuring Rational Antibacterial Prophylaxis and Therapy in the Neonatal Intensive Care Unit

commodate inclusion of patient characteristics to triage of patients according to international treatment guidelines.The genomic-GIS AI-driven technology can determine clinic catchment areas for accurate DR-TB incidences.The EPCON AI GIS algorithm can identify of areas vulnerable to DR-TB and DR-TB hotspots with Mycobacterium tuberculosis strains characterized by a SNP distance below 12.Discussion: there is both enthusiasm and scepticism surrounding AI technologies.We demonstrate that AI methods are relevant for translating genomic data into drug resistance profiles and supporting health care workers in making treatment decision for hardto-treat TB.Through the integration of three datasets that be defined as "big data" (mobility data, geospatial contextual data, genomic data), AI can synthesise and interpret large and interdependent datasets in a way that can be leveraged by public health institutes and national TB programs.Conclusion: Is possible to use AI and ML to inform precision medicine, precision public health, and drug resistance surveillance, in a way that conforms to the core WHO ethics and governance principles for AI.