1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.AI2023★ 1 cited
A optimization framework for herbal prescription planning based on deep reinforcement learning
Kuo Yang, Zecong Yu, Xin Su +7
Treatment planning for chronic diseases is a critical task in medical artificial intelligence, particularly in traditional Chinese medicine (TCM). However, generating optimized seq…
cs.AI2023
A Pre-training Framework for Knowledge Graph Completion
Kuan Xu, Kuo Yang, Hanyang Dong +3
Knowledge graph completion (KGC) is one of the effective methods to identify new facts in knowledge graph. Except for a few methods based on graph network, most of KGC methods tren…
cs.AI2023★ 1 cited
Knowledge Graph Completion based on Tensor Decomposition for Disease Gene Prediction
Xinyan Wang, Ting Jia, Chongyu Wang +5
Accurate identification of disease genes has consistently been one of the keys to decoding a disease's molecular mechanism. Most current approaches focus on constructing biological…