EHR-HGCN: An Enhanced Hybrid Approach for Text Classification Using Heterogeneous Graph Convolutional Networks in Electronic Health Records

EHR-HGCN: An Enhanced Hybrid Approach for Text Classification Using Heterogeneous Graph Convolutional Networks in Electronic Health Records

Information Science, Computer Science, Artificial Intelligence,
Electronic Health Records   Heterogeneous Graph Convolutional Networks   Text Classification   Natural Language Processing   Deep Learning  

EHR-HGCN: A Novel Hybrid Heterogeneous Graph Convolutional Network Method for Electronic Health Record Text Classification Academic Background With the rapid development of Natural Language Processing (NLP), text classification has become an important research direction in this field. Text classification not only helps us understand the knowledge b...

Inhibition Adaption on Pre-Trained Language Models

Information Science, Artificial Intelligence, Humanities and Others,
Pre-trained Language Models   Inhibition Adaption   Low Rank   Activation Functions   Text Classification   Question Answering Tasks  

InA: Inhibition Adaptation Method on Pre-trained Language Models Pre-trained Language Models (LMs) have achieved significant results in Natural Language Processing (NLP) tasks. However, traditional fine-tuning methods suffer from the problem of redundant parameters, which affects efficiency and effectiveness. To address this challenge, this paper p...