Incorporating Risk Factor Embeddings in Pre-trained Transformers Improves Sentiment Prediction in Psychiatric Discharge Summaries. - Xiyu Ding; Mei-Hua Hall; Timothy A. Miller (ClinicalNLP@EMNLP, 2020)

Understanding eConsult Triage Behavior with Natural Language Processing. - Xiyu Ding; Michael L. Barnett; Ateev Mehrotra; Timothy A. Miller (AMIA, 2020)

A machine learning methodology for real-time forecasting of the 2019-2020 COVID-19 outbreak using Internet searches, news alerts, and estimates from mechanistic models. - Dianbo Liu; Leonardo Clemente; Canelle Poirier; Xiyu Ding; Matteo Chinazzi; Jessica T. Davis; Alessandro Vespignani; Mauricio Santillana (CoRR, 2020)

Classifying Long Clinical Documents with Pre-trained Transformers. - Xin Su 008; Timothy Miller 002; Xiyu Ding; Majid Afshar; Dmitriy Dligach (CoRR, 2021)

Assessing the Impact of Social Determinants of Health on Patients with Type II Diabetes. - Xiyu Ding; Akihiko Nishimura; Scott Zeger; Hadi Kharrazi (AMIA, 2022)

Classifying unstructured electronic consult messages to understand primary care physician specialty information needs. - Xiyu Ding; Michael L. Barnett; Ateev Mehrotra; Delphine S. Tuot; Danielle S. Bitterman; Timothy A. Miller (J. Am. Medical Informatics Assoc., 2022)

Cross-Attention Fusion of MRI and Jacobian Maps for Alzheimer's Disease Diagnosis. - Shijia Zhang; Xiyu Ding; Brian Caffo; Junyu Chen; Cindy Zhang; Hadi Kharrazi; Zheyu Wang (CoRR, 2025)

ProtoBERT-LoRA: Parameter-Efficient Prototypical Finetuning for Immunotherapy Study Identification. - Shijia Zhang; Xiyu Ding; Kai Ding; Jacob Zhang; Kevin Galinsky; Mengrui Wang; Ryan P. Mayers; Zheyu Wang; Hadi Kharrazi (CoRR, 2025)