AMIA 2024
Implicit bias in patient-provider communication can lead to healthcare inequities, yet it is challenging to detect. Using ASR and NLP, we developed a pipeline to analyze social signals in audio recordings of 782 primary care visits, achieving 90.1% accuracy and fairness across patient groups. The analysis revealed significant disparities in provider behaviors, with more patient-centered communication observed toward white patients, highlighting the potential of automated tools to uncover biases and promote equitable healthcare.
CHI 2024
Analyzing patient-provider communication through social signals like dominance, interactivity, engagement, and warmth can help improve care by identifying opportunities for better interactions. We introduce a machine-learning pipeline embedded in ConverSense, a web application that visualizes communication patterns across visits. A user study with clinicians and patients highlights its potential to provide actionable, context-specific feedback for enhancing communication quality and patient outcomes.
CHI 2024
Implicit bias among healthcare providers can negatively impact care quality and patient outcomes, necessitating tools to identify and address these biases. Through design sessions with 24 primary care providers, we found they prefer feedback with transparent metrics, trends across visits, and actionable tips presented in a dashboard. These insights can guide the development of interactive systems to support equitable healthcare, especially for marginalized communities.
UIST 2023 Paper instructions are a mainstream medium for sharing knowledge. However, consuming such instructions and translating them into activities can be inefficient due to the lack of connectivity with the physical environment. PaperToPlace is a novel workflow comprising an authoring pipeline, which allows the authors to rapidly transform and spatialize existing paper instructions into an MR experience, and a consumption pipeline, which computationally places each instruction step at an optimal location that is easy to read and does not occlude key interaction areas. This is a collaborative project with Adobe Research.
ASSETS 2023 Assessing accessibility for wheelchair users can be challenging, due to lack of accessibility details needed for individual users. Embodied Exploration is a VR technique to deliver the experience of a physical visit while keeping the convenience of remote assessment. Embodied Exploration allows wheelchair users to explore high-fidelity digital replicas of physical environments with themselves embodied by avatars, leveraging the increasingly affordable VR headsets.