Minisymposium Presentation

High-quality, accurate, and real-time information about disease spread is critical for rapid response to a biothreat. Electronic health data is collected by approximately 90% of all physicians in the United States. However, its broad use for public health surveillance and monitoring is inhibited by a lack of organization around common and high-quality information. We use AI to automatically code unstructured clinical documents. During a biothreat scenario, these tools will help synthesize data across multiple medical records systems and enable the rapid identification of vulnerable populations. In addition to extracting important information from clinical records, we are developing an autonomous biothreat agent that scans reputable public health surveillance reports and identifies emerging threats. Once an emerging threat is identified, our AI agents will be able to search existing scientific literature to extract the disease specific parameters for epidemiological modeling. AI is helping us develop the necessary infrastructure for near real-time situational readiness, so that we will be prepared during the next Covid-like event.