Harnessing Machine Learning for Infectious Disease Management

Machine learning has the potential to enhance the diagnosis and treatment of infectious diseases by analyzing electronic health records (EHR) data. Specific cases, such as studying antimicrobial resistance through the connection of whole genome sequencing of pathogens like Staph aureus with EHR, show how insights can be derived from understanding patient profiles and treatment histories. This approach allows researchers to identify predictive features within EHR data that correlate with treatment outcomes and resistance patterns. Though EHR data contains valuable information, it often presents challenges such as biases and messy data that require careful handling to ensure accurate analyses.