Why Interface Design?
Today's systems are increasing in complexity. Technologically, we no longer suffer from a lack of data, but rather, lack of information due to large amounts of poorly presented data. To take advantage of large amounts of data, we need information displays that transform data into meaningful visualizations. This means developing performance-oriented displays that clearly connect performance goals to technical processes and equipment. The key is not to reduce data, but to transform it into meaningful information.
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Research Areas
Our focus is on interactive processes between technology and human users with the goal of developing high-end interfaces in the following domains:
News
Inter-University Workshop (IUW) 2025
Our Director, Dr. Catherine Burns, joined a group of graduate students to attend the 2025 Inter-University Workshop (IUW), hosted by the Human Factors Interest Group (HFIG) at the University of Toronto. The students had the opportunity to showcase their work, connect with peers, and gain new insights from inspiring presentations.
This scoping review evaluates recent advancements in data-driven technologies for predicting non-neonatal pediatric sepsis, including artificial intelligence, machine learning, and other methodologies. Of the 27 included studies, 23 (85%) were single-center investigations, and 16 (59%) used logistic regression. Notably, 20 (74%) studies used datasets with a low prevalence of sepsis-related outcomes, with area under the receiver operating characteristic scores ranging from 0.56 to 0.99. Prediction time points varied widely, and development characteristics, performance metrics, implementation outcomes, and considerations for human factors—especially workflow integration and clinical judgment—were inconsistently reported. The variations in endpoint definitions highlight the potential significance of the 2024 consensus criteria in future development. Future research should strengthen the involvement of clinical users to enhance the understanding and integration of human factors in designing and evaluating these technologies, ultimately aiming for safe and effective integration in pediatric healthcare.
Krizia Mae Francisco, a PhD member of our lab under the supervision of Professor Catherine M. Burns, in collaboration with Sabrina Saiko and Sormeh Mehri, Master’s students and lab members, published their findings in JMIR Publications! This research focuses on the protocol the team designed to understand how primary care clinicians respond to AI-enabled electronic medical record encounters.
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