UbiComp 2024
User preferences for mobile sensing and mental health interventions vary significantly across data types, with some sensors more acceptable than others. A university-wide survey reveals that individuals willing to share one type of data are often open to others, highlighting distinct engagement patterns. These insights support the design of inclusive, scalable mental health apps tailored to student needs.
AMIA 2024Implicit bias impacts the quality of patient-clinician interactions, influencing patient outcomes and trust in healthcare. Most interventions to mitigate bias rely solely on expensive human assessments, rather than leveraging AI technology with clinician input.
IJROBP 2024
Contouring assessments from novice radiation oncology residents reveal consistent patterns of error across disease sites, including undercontouring lymph nodes and missing key at-risk volumes. Using an interactive online platform during early clinical rotations, the study identifies specific structures frequently overlooked, such as the inguinal nodes in anal cancer and the base of skull in nasopharyngeal cases. These insights can inform targeted educational interventions and support the development of more standardized contouring curricula.