ReviseMate: Exploring Contextual Support for Digesting STEM Paper Reviews

Yuansong Xu, Shuhao Zhang, Yijie Fan, Shaohan Shi, Zhenhui Peng, Quan Li

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We developed ReviseMate, an interactive system designed for researchers to effectively assimilating and integrating reviewer feedback to refine their papers and handle potential rebuttal phases in academic venues. A controlled user study demonstrated the superiority of ReviseMate over baseline methods, with positive feedback regarding user interaction. Subsequent field deployment further validated the effectiveness of ReviseMate in real-world review digestion scenarios.

Advancing Problem-Based Learning with Clinical Reasoning for Improved Differential Diagnosis in Medical Education

Yuansong Xu, Yuheng Shao, Jiahe Dong, Shaohan Shi, Chang Jiang, Quan Li

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We designed e-MedLearn, a learner-centered PBL system that supports more efficient application and practice of evidence-based clinical reasoning. Through controlled study and testing interviews, we gathered data to assess the system’s impact. The findings demonstrate that e-MedLearn improves PBL experiences and provides valuable insights for advancing clinical reasoning-based learning.

CaseMaster: Designing a Probe for Oral Case Presentation Training with LLM Assistance

Yang Ouyang, Yuansong Xu, Chang Jiang, Quan Li PDF
We conducted a formative study with six medical educators and developed CaseMaster, an interactive probe that leverages LLM-generated content tailored to medical education to help users train their OCP skills. Through a preliminary user study from the expert perspective, we validated the effectiveness of the probe.

Medillustrator: Improving Retrospective Learning in Physicians’ Continuous Medical Education via Multimodal Diagnostic Data Alignment and Representation

Yuansong Xu, Jiahe Dong, Yijie Fan, Yuheng Shao, Chang Jiang, Lixia Jin, Yuanwu Cao, Quan Li

Preprint
We introduce Medillustrator, a visual analytics system crafted to facilitate novice physicians’ retrospective learning. Our structured approach enables novice physicians to explore and review research cases at an overview level and analyze specific cases with consistent alignment of multimodal and reference data. Furthermore, physicians can record and review analyzed results to facilitate further retrospection.

LiveRetro: Visual Analytics for Strategic Retrospect in Livestream E-Commerce

Yuchen Wu, Yuansong Xu, Shenghan Gao, Xingbo Wang, Wenkai Song, Zhiheng Nie, Xiaomeng Fan, Quan Li

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This study identified computational features, formulated design requirements, and developed LiveRetro , an interactive visual analytics system. It enables comprehensive retrospective analysis of livestream e-commerce for streamers, viewers, and merchandise. LiveRetro employs enhanced visualization and time-series forecasting models to align performance features and feedback, identifying influences at channel, merchandise, feature, and segment levels.