Artificial intelligence is constantly revolutionizing biomedical research and healthcare
management. Disease comorbidity is a major threat to the quality of life for susceptible …

Recent works reveal that network embedding techniques enable many machine learning
models to handle diverse downstream tasks on graph structured data. However, as previous …

摘要为解决在线文本中存在大量疾病指称的问题, 提出了基于多任务学习和多态语义特征的中文
疾病名称归一化模型(multi-task attention-dictionary BERT GRU-CNN, MTAD-BERT-GCNN) …

Recent works reveal that network embedding techniques enable many machine learning
models to handle diverse downstream tasks on graph-structured data. However, as previous …

Medical procedure entity normalization is an important task to realize medical information
sharing at the semantic level; it faces main challenges such as variety and similarity in real …

Objective Clinical narratives provide comprehensive patient information. Achieving
interoperability involves mapping relevant details to standardized medical vocabularies …

Stocks are typically linked with companies that have commercialized operations and are
establishing themselves in the business world. They can also be described as shares, a …

Medical concept normalization is a critical problem in biomedical research and clinical
applications. In this article, we focus on normalizing diagnostic and operation names in …

Medical entity normalization is a fundamental task in medical natural language processing
and clinical applications. The task aims to map medical mentions to standard entities in a …

Backgrounds Knowledge discovery from breast cancer treatment records has promoted
downstream clinical studies such as careflow mining and therapy analysis. However, the …