18 citations · 46 across the 6 of their papers we have counts for
6 papers
A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness
Fali Wang, Zhiwei Zhang, Xianren Zhang +11
Large language models (LLMs) have demonstrated emergent abilities in text generation, question answering, and reasoning, facilitating various tasks and domains. Despite their profi…
Explainable Diagnosis Prediction through Neuro-Symbolic Integration
Qiuhao Lu, Rui Li, Elham Sagheb +5
Diagnosis prediction is a critical task in healthcare, where timely and accurate identification of medical conditions can significantly impact patient outcomes. Traditional machine…
Large Language Models Struggle in Token-Level Clinical Named Entity Recognition
Qiuhao Lu, Rui Li, Andrew Wen +3
Large Language Models (LLMs) have revolutionized various sectors, including healthcare where they are employed in diverse applications. Their utility is particularly significant in…
Textual Data Augmentation for Patient Outcomes Prediction
Qiuhao Lu, Dejing Dou, Thien Huu Nguyen
Deep learning models have demonstrated superior performance in various healthcare applications. However, the major limitation of these deep models is usually the lack of high-quali…
Predicting Patient Readmission Risk from Medical Text via Knowledge Graph Enhanced Multiview Graph Convolution
Qiuhao Lu, Thien Huu Nguyen, Dejing Dou
Unplanned intensive care unit (ICU) readmission rate is an important metric for evaluating the quality of hospital care. Efficient and accurate prediction of ICU readmission risk c…
LNN-EL: A Neuro-Symbolic Approach to Short-text Entity Linking
Hang Jiang, Sairam Gurajada, Qiuhao Lu +5
Entity linking (EL), the task of disambiguating mentions in text by linking them to entities in a knowledge graph, is crucial for text understanding, question answering or conversa…