5 citations · 14 across the 9 of their papers we have counts for
10 papers
EpiScreen: Early Epilepsy Detection from Electronic Health Records with Large Language Models
Shuang Zhou, Kai Yu, Zaifu Zhan +5
Epilepsy and psychogenic non-epileptic seizures often present with similar seizure-like manifestations but require fundamentally different management strategies. Misdiagnosis is co…
HeartAgent: An Autonomous Agent System for Explainable Differential Diagnosis in Cardiology
Shuang Zhou, Kai Yu, Song Wang +11
Heart diseases remain a leading cause of morbidity and mortality worldwide, necessitating accurate and trustworthy differential diagnosis. However, existing artificial intelligence…
DrKGC: Dynamic Subgraph Retrieval-Augmented LLMs for Knowledge Graph Completion across General and Biomedical Domains
Yongkang Xiao, Sinian Zhang, Yi Dai +4
Knowledge graph completion (KGC) aims to predict missing triples in knowledge graphs (KGs) by leveraging existing triples and textual information. Recently, generative large langua…
EPEE: Towards Efficient and Effective Foundation Models in Biomedicine
Zaifu Zhan, Shuang Zhou, Huixue Zhou +2
Foundation models, including language models, e.g., GPT, and vision models, e.g., CLIP, have significantly advanced numerous biomedical tasks. Despite these advancements, the high…
An evaluation of DeepSeek Models in Biomedical Natural Language Processing
Zaifu Zhan, Shuang Zhou, Huixue Zhou +4
The advancement of Large Language Models (LLMs) has significantly impacted biomedical Natural Language Processing (NLP), enhancing tasks such as named entity recognition, relation…
A Review of Reinforcement Learning for Natural Language Processing, and Applications in Healthcare
Ying Liu, Haozhu Wang, Huixue Zhou +6
Reinforcement learning (RL) has emerged as a powerful approach for tackling complex medical decision-making problems such as treatment planning, personalized medicine, and optimizi…
Benchingmaking Large Langage Models in Biomedical Triple Extraction
Mingchen Li, Huixue Zhou, Rui Zhang
Biomedical triple extraction systems aim to automatically extract biomedical entities and relations between entities. The exploration of applying large language models (LLM) to tri…
PaniniQA: Enhancing Patient Education Through Interactive Question Answering
Pengshan Cai, Zonghai Yao, Fei Liu +9
Patient portal allows discharged patients to access their personalized discharge instructions in electronic health records (EHRs). However, many patients have difficulty understand…
W-procer: Weighted Prototypical Contrastive Learning for Medical Few-Shot Named Entity Recognition
Mingchen Li, Yang Ye, Jeremy Yeung +3
Contrastive learning has become a popular solution for few-shot Name Entity Recognization (NER). The conventional configuration strives to reduce the distance between tokens with t…
Complementary and Integrative Health Lexicon (CIHLex) and Entity Recognition in the Literature
Huixue Zhou, Robin Austin, Sheng-Chieh Lu +5
Objective: Our study aimed to construct an exhaustive Complementary and Integrative Health (CIH) Lexicon (CIHLex) to better represent the often underrepresented physical and psycho…