activity
20232026
most citedDrKGC: Dynamic Subgraph Retrieval-Augmented LLMs for Knowledge Graph Completion across General and Biomedical Domains

5 citations · 14 across the 9 of their papers we have counts for

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8 papers · 1 filter

cs.CL2026

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…

cs.CL2026

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…

cs.CL2025★ 1 cited

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…

cs.CL2023★ 4 cited

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…

cs.CL2023★ 3 cited

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…

cs.CL2023

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…