21 citations · 21 across the 5 of their papers we have counts for
5 papers
Rethinking the UI of GenUI: A Tale of Two Designs
Xiang 'Anthony' Chen, Savvas Dimitrios Petridis, Tian Deng +3
GenUI is an emergent class of AI tools that use large models to generate UI mock-ups based on users' high-level descriptions, promising to democratize UX design exploration for a b…
Z-Stack Scanning can Improve AI Detection of Mitosis: A Case Study of Meningiomas
Hongyan Gu, Ellie Onstott, Wenzhong Yan +5
Z-stack scanning is an emerging whole slide imaging technology that captures multiple focal planes alongside the z-axis of a glass slide. Because z-stacking can offer enhanced dept…
The GenUI Study: Exploring the Design of Generative UI Tools to Support UX Practitioners and Beyond
Xiang 'Anthony' Chen, Tiffany Knearem, Yang Li
AI can now generate high-fidelity UI mock-up screens from a high-level textual description, promising to support UX practitioners' work. However, it remains unclear how UX practiti…
Supporting Mitosis Detection AI Training with Inter-Observer Eye-Gaze Consistencies
Hongyan Gu, Zihan Yan, Ayesha Alvi +6
The expansion of artificial intelligence (AI) in pathology tasks has intensified the demand for doctors' annotations in AI development. However, collecting high-quality annotations…
Majority Voting of Doctors Improves Appropriateness of AI Reliance in Pathology
Hongyan Gu, Chunxu Yang, Shino Magaki +17
As Artificial Intelligence (AI) making advancements in medical decision-making, there is a growing need to ensure doctors develop appropriate reliance on AI to avoid adverse outcom…