Clinical decision support: We design and study rule-based and AI-based clinical decision support tools which are deployed through EHRs to help clinicians make better diagnosis, treatment and screening decisions, and
Clinical machine learning: With the adoption of EHRs, we now routinely collect terabytes of data on patients, including medications, problems, test results, images and clinical narratives. Our group designs and evaluates new machine learning algorithms to make sense of this data, detect patterns and spot opportunities to intervene and improve care.
Safe and effective use of EHRs: We are designing new workflows and user interactions for EHRs that are faster, more accurate and more enjoyable, and studying them in the real world. Recent projects have focused on improving the display of microbiology data, making problem lists work better and redesigning medication ordering workflows.
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