1 citations · 1 across the 4 of their papers we have counts for
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"Do I Trust the AI?" Towards Trustworthy AI-Assisted Diagnosis: Understanding User Perception in LLM-Supported Reasoning
Yuansong Xu, Yichao Zhu, Haokai Wang +7
Large language models (LLMs) have shown considerable potential in supporting medical diagnosis. However, their effective integration into clinical workflows is hindered by physicia…
CommSense: Facilitating Bias-Aware and Reflective Navigation of Online Comments for Rational Judgment
Yang Ouyang, Shenghan Gao, Ruichuan Wang +4
Online comments significantly influence users' judgments, yet their presentation, often determined by platform algorithms, can introduce biases, such as anchoring effects, which di…
CaseMaster: Designing and Evaluating a Probe for Oral Case Presentation Training with LLM Assistance
Yang Ouyang, Yuansong Xu, Chang Jiang +3
Preparing an oral case presentation (OCP) is a crucial skill for medical students, requiring clear communication of patient information, clinical findings, and treatment plans. How…
NotePlayer: Engaging Jupyter Notebooks for Dynamic Presentation of Analytical Processes
Yang Ouyang, Leixian Shen, Yun Wang +1
Diverse presentation formats play a pivotal role in effectively conveying code and analytical processes during data analysis. One increasingly popular format is tutorial videos, pa…
A Two-Phase Visualization System for Continuous Human-AI Collaboration in Sequelae Analysis and Modeling
Yang Ouyang, Chenyang Zhang, He Wang +7
In healthcare, AI techniques are widely used for tasks like risk assessment and anomaly detection. Despite AI's potential as a valuable assistant, its role in complex medical data…