no code implementations • 9 Dec 2023 • Rumeng Li, Xun Wang, Hong Yu
We train a system to detect AD-related signs and symptoms from EHRs, using three datasets: (1) a gold dataset annotated by human experts on longitudinal EHRs of AD patients; (2) a silver dataset created by the data-to-label method; and (3) a bronze dataset created by the label-to-data method.
1 code implementation • 24 Oct 2023 • Junda Wang, Zonghai Yao, Zhichao Yang, Huixue Zhou, Rumeng Li, Xun Wang, Yucheng Xu, Hong Yu
We introduce NoteChat, a novel cooperative multi-agent framework leveraging Large Language Models (LLMs) to generate patient-physician dialogues.
no code implementations • 23 Jul 2023 • Rumeng Li, Xun Wang, Dan Berlowitz, Brian Silver, Wen Hu, Heather Keating, Raelene Goodwin, Weisong Liu, Honghuang Lin, Hong Yu
We used a panel of AD-related keywords and their occurrences over time in a patient's longitudinal EHRs as predictors for AD prediction with four machine learning models.
no code implementations • 11 Dec 2019 • Rumeng Li, Xun Wang, Hong Yu
Manipulating training data leads to robust neural models for MT.
no code implementations • 8 Dec 2013 • Rumeng Li, Tao Wang, Xun Wang
Existing approaches neglect such hierarchical topic structure involved in the news corpus in timeline generation.