Label Dependent Attention Model for Disease Risk Prediction Using Multimodal Electronic Health Records

Keyphrases

• Electronic Health Records 100%
• Attention Model 100%
• Disease Risk Prediction 100%
• Medical Notes 100%
• Prediction Task 66%
• Risk Prediction 66%
• Prediction Skill 33%
• Predictive Power 33%
• Artificial Intelligence 33%
• Language Model 33%
• Joint Embedding 33%
• Disease Risk 33%
• Time Series Data 33%
• Result Prediction 33%
• Attention Mechanism 33%
• Multimodal Learning 33%
• Modern Healthcare 33%
• Attention Module 33%
• Artificial Intelligence Models 33%
• Clinical BERT 33%
• Heterogeneous Patients 33%
• Heterogeneous Information 33%
• Patient Information 33%
• Prediction Label 33%
• Health Status Indicators 33%

Computer Science

• Interpretability 100%
• Case Study 33%
• Learning Framework 33%
• Artificial Intelligence 33%
• Attention (Machine Learning) 33%
• Word Embedding 33%
• Predictive Power 33%
• Time Series Data 33%
• Multimodal Learning 33%
• Bidirectional Encoder Representations From Transformers 33%
• Artificial Intelligence Model 33%
• Patient Information 33%
• Pre-Trained Language Models 33%

Mathematics

• Interpretability 100%
• Time Series Data 33%
• Word Embedding 33%
• Predictive Power 33%
• Time Series 33%
• Time Series Analysis 33%
• Multimodal Learning 33%