MR-KPA: medication recommendation by combining knowledge-enhanced pre-training with a deep adversarial network.

Background: Medication recommendation based on electronic medical record (EMR) is a research hot spot in smart healthcare. For developing computational medication recommendation methods based on EMR, an important challenge is the lack of a large number of longitudinal EMR data with time correlation. Faced with this challenge, this paper proposes a new EMR-based medication recommendation model called MR-KPA, which combines knowledge-enhanced pre-training with the deep adversarial network to improve medication recommendation from both feature representation and the fine-tuning process.

Combining knowledge graph with deep adversarial network for water quality prediction.

Water quality prediction is an important research focus in smart water and can provide the support to control and reduce water pollution. However, existing water quality prediction models are mainly data-driven and only rely on various sensor data. This paper proposes a new water quality prediction modeling approach integrating data and knowledge.