Research

Publications

• Tongnian Wang, Kai Zhang, Jiannan Cai, Yanmin Gong, Kim-Kwang Raymond Choo, Yuanxiong Guo. Analyzing the Impact of Personalization on Fairness in Federated Learning for Healthcare. Journal of Healthcare Informatics Research (JHIR), 2024.

• Tongnian Wang, Yan Du, Yanmin Gong, Kim-Kwang Raymond Choo, Yuanxiong Guo. Applications of Federated Learning in Mobile Health: Scoping Review. Journal of Medical Internet Research (JMIR), 2023.

• Tongnian Wang, Xingmeng Zhao, Anthony Rio. UTSA-NLP at RadSum23: Multi-modal Retrieval-Based Chest X-Ray Report Summarization. The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks (BioNLP), 2023.

• Xingmeng Zhao, Tongnian Wang, Sheri Osborn, Anthony Rio. BabyStories: Can Reinforcement Learning Teach Baby Language Models to Write Better Stories?. The BabyLM Challenge at the 27th Conference on Computational Natural Language Learning, (CoNLL 2023), 2023.

• Tongnian Wang, Yuanxiong Guo, Kim-Kwang Raymond Choo. Enabling Privacy-Preserving Prediction for Length of Stay in ICU-A Multimodal Federated-Learning-based Approach. European Conference on Information Systems (ECIS), 2023.

Under Review & In Preparation

• X. Zhao, T. Wang, A. Rios. Improving Expert Radiology Report Summarization by Prompting Large Language Models with a Layperson Summary. Under Review.

• T. Wang et al. FairPFL: A Fairness-Aware Personalized Federated Learning Approach for Clinical Outcome Prediction in Intensive Care Unit. Under Review.

• T. Wang et al. Algorithmic Bias in Machine Learning Models for Predicting Opioid Use Disorder Treatment Discontinuation. Under Review.