Classifying social determinants of health from unstructured electronic health records using deep learning-based natural language processing [0.03%]
基于深度学习的自然语言处理在未结构化的电子健康记录中划分社会健康决定因素
Sifei Han,Robert F Zhang,Lingyun Shi et al.
Sifei Han et al.
Objective: Social determinants of health (SDOH) are non-medical factors that can profoundly impact patient health outcomes. However, SDOH are rarely available in structured electronic health record (EHR) data such as diag...
An annotated corpus from biomedical articles to construct a drug-food interaction database [0.03%]
一个注解语料库：来自生物医学期刊的药物与食物相互作用数据库的构建
Siun Kim,Yoona Choi,Jung-Hyun Won et al.
Siun Kim et al.
Motivation: While drug-food interaction (DFI) may undermine the efficacy and safety of drugs, DFI detection has been difficult because a well-organized database for DFI did not exist. To construct a DFI database and build...
Stratifying individuals into non-alcoholic fatty liver disease risk levels using time series machine learning models [0.03%]
基于时间序列机器学习模型的非酒精性脂肪肝风险分层研究
Ofir Ben-Assuli,Arie Jacobi,Orit Goldman et al.
Ofir Ben-Assuli et al.
Non-alcoholic fatty liver disease (NAFLD) affects 25% of the population worldwide, and its prevalence is anticipated to increase globally. While most NAFLD patients are asymptomatic, NAFLD may progress to fibrosis, cirrhosis, cardiovascular...
High-quality gene/disease embedding in a multi-relational heterogeneous graph after a joint matrix/tensor decomposition [0.03%]
联合矩阵/张量分解后的异构多关系图中的高质量基因/疾病嵌入模型
Kaiyin Zhou,Sheng Zhang,Yuxing Wang et al.
Kaiyin Zhou et al.
Motivation: Node embedding of biological entity network has been widely investigated for the downstream application scenarios. To embed full semantics of gene and disease, a multi-relational heterogeneous graph is conside...
CODER: Knowledge-infused cross-lingual medical term embedding for term normalization [0.03%]
基于知识的跨语言医学术语嵌入规范化方法
Zheng Yuan,Zhengyun Zhao,Haixia Sun et al.
Zheng Yuan et al.
Objective: This paper aims to propose knowledge-aware embedding, a critical tool for medical term normalization. Methods: We develop CO...
AMMU: A survey of transformer-based biomedical pretrained language models [0.03%]
基于变压器的生物医学预训练语言模型综述（AMMU）
Katikapalli Subramanyam Kalyan,Ajit Rajasekharan,Sivanesan Sangeetha
Katikapalli Subramanyam Kalyan
Transformer-based pretrained language models (PLMs) have started a new era in modern natural language processing (NLP). These models combine the power of transformers, transfer learning, and self-supervised learning (SSL). Following the suc...
Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies [0.03%]
电子健康记录中深度学习在时间序列数据表示中的挑战和方法学：系统综述
Feng Xie,Han Yuan,Yilin Ning et al.
Feng Xie et al.
Objective: Temporal electronic health records (EHRs) contain a wealth of information for secondary uses, such as clinical events prediction and chronic disease management. However, challenges exist for temporal data repre...
Giorgio Leonardi,Stefania Montani,Manuel Striani
Giorgio Leonardi
Medical process trace classification exploits the activity sequences logged by an healthcare organization to classify traces themselves on the basis of some performance properties; this information can be used for quality assessment. State-...
Multi-level process mining methodology for exploring disease-specific care processes [0.03%]
多级过程挖掘方法，用于探索基于疾病的特异性护理流程
Ágnes Vathy-Fogarassy,István Vassányi,István Kósa
Ágnes Vathy-Fogarassy
Background: Public healthcare is a complex domain with many actors and highly variable protocols, which makes traditional process mining tools less effective and calls for specialized methods. ...
Multi-view prediction of Alzheimer's disease progression with end-to-end integrated framework [0.03%]
基于端到端集成框架的阿尔茨海默病进展的多视角预测
Yan Zhao,Baoqiang Ma,Tongtong Che et al.
Yan Zhao et al.
Alzheimer's disease is a common neurodegenerative brain disease that affects the elderly population worldwide. Its early automatic detection is vital for early intervention and treatment. A common solution is to perform future cognitive sco...