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The aim of this project was to create time-aware, individual-level risk score models for adverse drug events related to multiple sclerosis disease-modifying therapy and to provide interpretable explanations for model prediction behavior.

To explore the feasibility of validating Dutch concept extraction tools using annotated corpora translated from English, focusing on preserving annotations during translation and addressing the scarcity of non-English annotated clinical corpora.

 Blood product ordering is a complex process and mistakes can harm patients and lead to poor outcomes. Orders and order sets can be designed to help mitigate errors, but major changes in design can unintentionally cause new errors.

To use workflow execution models to highlight new considerations for patient-centered clinical decision support policies (PC CDS), processes, procedures, technology, and expertise required to support new workflows.

Develop a novel technique to identify an optimal number of regression units corresponding to a single risk point, while creating risk scoring systems from logistic regression-based disease predictive models. The optimal value of this hyperparameter balances simplicity and accuracy, yielding risk scores of small scale and high accuracy for patient risk stratification.

 This study aimed to increase the adoption of revised newborn hyperbilirubinemia guidelines by building a clinical decision support (CDS) tool into templated notes.

Numerous programs have arisen to address interruptive clinical decision support (CDS) with the goals of reducing alert burden and alert fatigue. These programs often have standing committees with broad stakeholder representation, significant governance efforts, and substantial analyst hours to achieve reductions in alert burden which can be difficult for hospital systems to replicate.

To explore the feasibility and challenges of mapping between SNOMED CT and the ICD-11 Foundation in both directions, SNOMED International and the World Health Organization conducted a pilot mapping project between September 2021 and August 2022.

To address challenges in large-scale electronic health record (EHR) data exchange, we sought to develop, deploy, and test an open source, cloud-hosted app "listener" that accesses standardized data across the SMART/HL7 Bulk FHIR Access application programming interface (API).