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Medical knowledge graph construction by aligning large biomedical datasets

Michael Röder, Giorgos Stoilos, David Geleta, Jetendr Shamdasani, Mohammad Khodadadi
2018 International Semantic Web Conference  
Extended Abstract Building large Knowledge Bases can be realised by aligning and integrating existing data sources.  ...  To support AI-based digital healthcare services within Babylon Health 1 significant effort to build a large medical KB was recently undertaken.  ... 
dblp:conf/semweb/RoderSGSK18 fatcat:iq3fddnq55g4xpkfbfbwzdkxmi

Self-Alignment Pretraining for Biomedical Entity Representations [article]

Fangyu Liu, Ehsan Shareghi, Zaiqiao Meng, Marco Basaldella, Nigel Collier
2021 arXiv   pre-print
To address this challenge, we propose SapBERT, a pretraining scheme that self-aligns the representation space of biomedical entities.  ...  six MEL benchmarking datasets.  ...  Medical entity linking is a segue to tackle this problem by framing it as a task of mapping entity mentions to unified concepts in a medical knowledge graph.  ... 
arXiv:2010.11784v2 fatcat:ln7msidxuvdxfeudcf5opyxlqa

KGHC: a knowledge graph for hepatocellular carcinoma

Nan Li, Zhihao Yang, Ling Luo, Lei Wang, Yin Zhang, Hongfei Lin, Jian Wang
2020 BMC Medical Informatics and Decision Making  
To this purpose, we constructed a knowledge graph for Hepatocellular Carcinoma (KGHC). We propose an approach to build a knowledge graph for hepatocellular carcinoma.  ...  Mining relative medical knowledge from rapidly growing text data and integrating it with other existing biomedical resources will provide support to the research on the hepatocellular carcinoma.  ...  About this supplement This article has been published as part of BMC Medical Informatics and Decision Making Volume 20 Supplement 3, 2020: Health Information Processing.  ... 
doi:10.1186/s12911-020-1112-5 pmid:32646496 fatcat:sfe6p63dfvbnxldi6ubdyllhwy

Integrating Graph Contextualized Knowledge into Pre-trained Language Models [article]

Bin He, Di Zhou, Jinghui Xiao, Xin jiang, Qun Liu, Nicholas Jing Yuan, Tong Xu
2021 arXiv   pre-print
Complex node interactions are common in knowledge graphs, and these interactions also contain rich knowledge information.  ...  Experimental results demonstrate that our model achieves the state-of-the-art performance on several medical NLP tasks, and improvement above TransE indicates that our KRL method captures the graph contextualized  ...  Experiments Dataset Medical Knowledge Graph The Unified Medical Language System (UMLS) (Bodenreider 2004 ) is a comprehensive knowledge base in the biomedical domain, which contains large-scale concept  ... 
arXiv:1912.00147v3 fatcat:7ovn5wag2nb4vpjhz6hjnyysla

Incorporating Domain Knowledge into Medical NLI using Knowledge Graphs

Soumya Sharma, Bishal Santra, Abhik Jana, Santosh Tokala, Niloy Ganguly, Pawan Goyal
2019 Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)  
In this paper, we explore how to incorporate structured domain knowledge, available in the form of a knowledge graph (UMLS), for the Medical NLI task.  ...  Experiments conducted on MedNLI dataset clearly show that this strategy improves the baseline BioELMo architecture for the Medical NLI task 1 .  ...  Constructing the appropriate knowledge graph: We use the MetaMap tool to process the complete MedNLI dataset and extract the relevant information from UMLS into a smaller knowledge graph.  ... 
doi:10.18653/v1/d19-1631 dblp:conf/emnlp/SharmaSJTGG19 fatcat:66dxuxugujc5nhjj2oso2wv4dq

Incorporating Domain Knowledge into Medical NLI using Knowledge Graphs [article]

Soumya Sharma, Bishal Santra, Abhik Jana, T.Y.S.S. Santosh, Niloy Ganguly, Pawan Goyal
2019 arXiv   pre-print
In this paper, we explore how to incorporate structured domain knowledge, available in the form of a knowledge graph (UMLS), for the Medical NLI task.  ...  Experiments conducted on MedNLI dataset clearly show that this strategy improves the baseline BioELMo architecture for the Medical NLI task.  ...  Constructing the appropriate knowledge graph: We use the MetaMap tool to process the complete MedNLI dataset and extract the relevant information from UMLS into a smaller knowledge graph.  ... 
arXiv:1909.00160v1 fatcat:veiqtllljzcqjdqn3avzbyyphu

A Review on the Application of Knowledge Graph Technology in the Medical Field

Jia Qu, Jianping Gou
2022 Scientific Programming  
Medicine is one of the widely used fields of knowledge graphs, and the construction of a medical knowledge graph is also a research hotspot in artificial intelligence.  ...  Finally, with the major challenges and key problems of the current medical knowledge graph construction technology, its development prospects are prospects.  ...  of medical knowledge graph construction.  ... 
doi:10.1155/2022/3212370 fatcat:hkn7qal4yrfcdlbstpqlvddr7q

HKGB: An Inclusive, Extensible, Intelligent, Semi-auto-constructed Knowledge Graph Framework for Healthcare with Clinicians' Expertise Incorporated

Yong Zhang, Ming Sheng, Rui Zhou, Ye Wang, Guangjie Han, Han Zhang, Chunxiao Xing, Jing Dong
2020 Information Processing & Management  
Acknowledgement This work is supported by ARC Discovery Projects under Grant No. DP170104747, DP180100212 and DP200103700.  ...  How to build a semi-auto-constructed knowledge graph framework in the medical domain? 2. How to integrate the clinicians' prior knowledge into the construction of health knowledge graphs? 3.  ...  We provide an inclusive, intelligent, semi-auto-constructed knowledge graph framework HKGB for the medical domain to build knowledge graphs. 2.  ... 
doi:10.1016/j.ipm.2020.102324 fatcat:ueralf7xdrbylbpavn63gya6w4

Recent Advances in Automated Question Answering In Biomedical Domain [article]

Krishanu Das Baksi
2021 arXiv   pre-print
In this paper, we introduce the basic methodologies used for developing general domain QA systems, followed by a thorough investigation of different aspects of biomedical QA systems, including benchmark  ...  datasets and several proposed approaches, both using structured databases and collection of texts.  ...  [212, 211] . • Medical Examination: These datasets are constructed from questions asked in medical certification or other associated exams.  ... 
arXiv:2111.05937v1 fatcat:5474jk6ozbalvmfjrgatu4tsna

PatientEG Dataset: Bringing Event Graph Model with Temporal Relations to Electronic Medical Records [article]

Xuli Liu and Jihao Jin and Qi Wang and Tong Ruan and Yangming Zhou and Daqi Gao and Yichao Yin
2018 arXiv   pre-print
To help to normalize entity values which contain synonyms, hyponymies, and abbreviations, we link them with the Chinese biomedical knowledge graph.  ...  Based on the proposed model, we also construct a PatientEG dataset with 191,294 events, 3,429 distinct entities, and 545,993 temporal relations using EMRs from Shanghai Shuguang hospital.  ...  We have released a Chinese biomedical knowledge graph (CBioMedKG) in our prior work [17] .  ... 
arXiv:1812.09905v1 fatcat:edbkylbpzrcy3lsawcx4yzppjq

An automatic approach for constructing a knowledge base of symptoms in Chinese

Tong Ruan, Mengjie Wang, Jian Sun, Ting Wang, Lu Zeng, Yichao Yin, Ju Gao
2017 Journal of Biomedical Semantics  
While a large number of well-known knowledge bases (KBs) in life science have been published as Linked Open Data, there are few KBs in Chinese.  ...  Methods: Firstly, we design data schema manually by reference to the Unified Medical Language System (UMLS).  ...  About this supplement This article has been published as part of Journal of Biomedical Semantics Volume 8 Supplement 1, 2017: Selected articles from the Biological Ontologies and Knowledge bases workshop  ... 
doi:10.1186/s13326-017-0145-x pmid:29297414 pmcid:PMC5763289 fatcat:5ay64otwjjadndjsh5wbdvwuuu

COVID-19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature [article]

Colby Wise, Vassilis N. Ioannidis, Miguel Romero Calvo, Xiang Song, George Price, Ninad Kulkarni, Ryan Brand, Parminder Bhatia, George Karypis
2020 arXiv   pre-print
In this work, we present the COVID-19 Knowledge Graph (CKG), a heterogeneous graph for extracting and visualizing complex relationships between COVID-19 scientific articles.  ...  The CKG is constructed using the latent schema of the data, and then enriched with biomedical entity information extracted from the unstructured text of articles using scalable AWS technologies to form  ...  Part one validates the construction and curation of the CKG by showing article topics align with common subject focuses of scientific journals and CKG relations are high quality.  ... 
arXiv:2007.12731v1 fatcat:shbewuzebrctxgsa3dhnsl623q

Head and Tail Entity Fusion Model in Medical Knowledge Graph Construction: Case Study in Pituitary Adenoma (Preprint)

An Fang, Pei Lou, Jiahui Hu, Wanqing Zhao, Ming Feng, Huiling Ren, Xianlai Chen
2021 JMIR Medical Informatics  
Construct a pituitary adenoma knowledge graph, and use the knowledge graph for knowledge discovery.  ...  In this paper, a complete framework suitable for the construction of medical knowledge graph was presented, and used to build a knowledge graph for pituitary adenoma(KGPA).  ...  This enabled obtaining sufficient medical knowledge to construct the knowledge graph.  ... 
doi:10.2196/28218 pmid:34057414 fatcat:cptryunflfezngiyswddsnzccu

Drugs4Covid: Drug-driven Knowledge Exploitation based on Scientific Publications [article]

Carlos Badenes-Olmedo, David Chaves-Fraga, MarÍa Poveda-VillalÓn, Ana Iglesias-Molina, Pablo Calleja, Socorro Bernardos, Patricia MartÍn-Chozas, Alba Fernández-Izquierdo, Elvira Amador-Domínguez, Paola Espinoza-Arias, Luis Pozo, Edna Ruckhaus (+4 others)
2020 arXiv   pre-print
An open catalogue of drugs has been created and results are publicly available through a drug browser, a keyword-guided text explorer, and a knowledge graph.  ...  In the absence of sufficient medication for COVID patients due to the increased demand, disused drugs have been employed or the doses of those available were modified by hospital pharmacists.  ...  Knowledge Graph Construction The D4C-KG contains RDF annotations extracted from the CORD-19 dataset that are described by the D4C vocabulary.  ... 
arXiv:2012.01953v1 fatcat:up7yubpflvfk7iqvblirofvwy4

A Concise Survey on Datasets, Tools and Methods for Biomedical Text

R. Johnsi, G. Bharadwaja Kumar, Tulasi Prasad Sariki
2022 International Journal of Applied Engineering Research  
Analyzing such information could help us to come across new Biomedical knowledge such as drug discovery, drug-disease interactions, adverse drug reactions and realization of patient conditions.  ...  Biomedical text mining aims to retrieve useful information from large data efficiently and convert it into practical usage in a way of diagnosing symptoms, prevention, and treatment of diseases.  ...  medical records, this knowledge tends to be biased and out of date. 4) As Biomedical domain is very vast domain.  ... 
doi:10.37622/ijaer/17.3.2022.200-217 fatcat:2cw7f572rjfqvbnbrpq7gc75ue
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