Bioie: Biomedical information extraction with multi-head attention enhanced graph convolutional network
J Wu, R Zhang, T Gong, Y Liu… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Constructing large-scaled medical knowledge graphs (MKGs) can significantly boost
healthcare applications for medical surveillance, bring much attention from recent research …
healthcare applications for medical surveillance, bring much attention from recent research …
Delineation of ischemic lesion from brain MRI using attention gated fully convolutional network
R Karthik, M Radhakrishnan, R Rajalakshmi… - Biomedical Engineering …, 2021 - Springer
Precise delineation of the ischemic lesion from unimodal Magnetic Resonance Imaging
(MRI) is a challenging task due to the subtle intensity difference between the lesion and …
(MRI) is a challenging task due to the subtle intensity difference between the lesion and …
Interpretable machine learning methods for in vitro pharmaceutical formulation development
Background Machine learning has become an alternative approach for pharmaceutical
formulation development. However, many machine learning applications in pharmaceutics …
formulation development. However, many machine learning applications in pharmaceutics …
Extraction of causal relations based on SBEL and BERT model
Extraction of causal relations between biomedical entities in the form of Biological
Expression Language (BEL) poses a new challenge to the community of biomedical text …
Expression Language (BEL) poses a new challenge to the community of biomedical text …
FoodChem: A food-chemical relation extraction model
In this paper, we present FoodChem, a new Relation Extraction (RE) model for identifying
chemicals present in the composition of food entities, based on textual information provided …
chemicals present in the composition of food entities, based on textual information provided …
Auto-learning convolution-based graph convolutional network for medical relation extraction
M Qian, J Wang, H Lin, D Zhao, Y Zhang… - … Retrieval: 27th China …, 2021 - Springer
Medical relation extraction discovers relations between entity mentions in unstructured text,
such as biomedical literature. Dependency structures have proven to be useful for this task …
such as biomedical literature. Dependency structures have proven to be useful for this task …
Deep semi-supervised learning ensemble framework for classifying co-mentions of human proteins and phenotypes
M Pourreza Shahri, I Kahanda - BMC bioinformatics, 2021 - Springer
Background Identifying human protein-phenotype relationships has attracted researchers in
bioinformatics and biomedical natural language processing due to its importance in …
bioinformatics and biomedical natural language processing due to its importance in …
[PDF][PDF] 基于最短依存路径和集成学习的化学物蛋白质关系抽取
程威， 邵一帆， 钱龙华， 周国栋 - 中文信息学报, 2021 - jcip.cipsc.org.cn
化学物与蛋白质之间的相互作用关系抽取对精准医学和药物发现等方面的研究有着重要作用.
该文提出了一种基于最短依存路径和注意力机制的双向LSTM 模型, 并将其应用于化学物蛋白质 …
该文提出了一种基于最短依存路径和注意力机制的双向LSTM 模型, 并将其应用于化学物蛋白质 …
[PDF][PDF] A multi-task transfer learning-based method for extracting drug-protein interactions
E El-allaly, M Sarrouti… - Proceedings …, 2021 - biocreative.bioinformatics.udel.edu
Automatic extraction of the relationship between drugs/chemicals and proteins from
biomedical literature is a crucial task for drug discovery and drug-induced adverse reactions …
biomedical literature is a crucial task for drug discovery and drug-induced adverse reactions …