Distributed representations of diseases based on co-occurrence relationship
作者：
Highlights：
• Co-occurrence among diseases is crucial to knowledge discovery in medicine.
• Existing researches are mainly based on clinical experience rather than data driven.
• The distance in the disease embedding space reflects the co-occurrence relationship.
• Existing medical concept embedding models focus on prediction tasks.
• The first work to use disease embedding to study co-occurrence relationships.
摘要
•Co-occurrence among diseases is crucial to knowledge discovery in medicine.•Existing researches are mainly based on clinical experience rather than data driven.•The distance in the disease embedding space reflects the co-occurrence relationship.•Existing medical concept embedding models focus on prediction tasks.•The first work to use disease embedding to study co-occurrence relationships.
论文关键词：Disease embedding,Co-occurrence relationship,Knowledge discovery,Markov random fields
论文评审过程：Received 23 November 2020, Revised 22 April 2021, Accepted 9 June 2021, Available online 20 June 2021, Version of Record 23 June 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115418
