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Medical knowledge graph construction by aligning large biomedical datasets
2018
International Semantic Web Conference
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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]
2021
arXiv
pre-print
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2020 pre-print arXiv:2010.11784v1 fatcat:xkw5p2kr2jgn5gf7v2csnrpf7u
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
2020
BMC Medical Informatics and Decision Making
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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]
2021
arXiv
pre-print
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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
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)
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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]
2019
arXiv
pre-print
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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
2022
Scientific Programming
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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
2020
Information Processing & Management
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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]
2021
arXiv
pre-print
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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]
2018
arXiv
pre-print
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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
2017
Journal of Biomedical Semantics
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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]
2020
arXiv
pre-print
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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)
2021
JMIR Medical Informatics
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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]
2020
arXiv
pre-print
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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
2022
International Journal of Applied Engineering Research
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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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