Knowledge Graph In Health Care
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Healthcare knowledge graph construction: A systematic …
(4 days ago) WebKnowledge graphs (KGs) have proven utility in this arena and are rooted in a number of healthcare applications to furnish better data representation and knowledge inference. However, in conjunction with a lack of a representative KG construction …
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10225120/
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Healthcare knowledge graph construction: A systematic review of …
(7 days ago) WebThe incorporation of data analytics in the healthcare industry has made significant progress, driven by the demand for efficient and effective big data analytics solutions. Knowledge graphs (KGs) have proven utility in this arena and are rooted in a number of healthcare applications to furnish better data representation and knowledge …
https://journalofbigdata.springeropen.com/articles/10.1186/s40537-023-00774-9
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Building a knowledge graph to enable precision medicine
(Just Now) WebKnowledge-driven drug repurposing using a comprehensive drug knowledge graph. Health Informatics Journal 26 , 2737–2750 (2020). Article Google Scholar
https://www.nature.com/articles/s41597-023-01960-3
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Personalized Health Knowledge Graph - PMC - National …
(3 days ago) WebPersonalized Healthcare Knowledge Graph (PHKG) 8 is a representation of all relevant medical knowledge and personal data for a patient. PHKG can support development of innovative applications such as digitalized personalized coach applications that can keep patients informed and help manage their chronic condition, and empower the physicians …
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8532078/
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HealthPathFinder: Navigating the Healthcare Knowledge …
(2 days ago) WebIncorporating Knowledge Graphs (KGs) in healthcare recommender systems offers a powerful means to address the complexities of patient health data. By harnessing the interlinks within a KG, novel paths that connect patients and healthcare items (e.g., treatments or medications) can be discovered. These paths provide …
https://link.springer.com/chapter/10.1007/978-3-031-53824-7_40
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[2207.03771] Healthcare Knowledge Graph Construction: …
(2 days ago) WebThe incorporation of data analytics in the healthcare industry has made significant progress, driven by the demand for efficient and effective big data analytics solutions. Knowledge graphs (KGs) have proven utility in this arena and are rooted in a number of healthcare applications to furnish better data representation and knowledge …
https://arxiv.org/abs/2207.03771
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From Data to Wisdom: Biomedical Knowledge Graphs for …
(Just Now) WebGraph data models are an emerging approach to structure clinical and biomedical information. These models offer intriguing opportunities for novel approaches in healthcare, such as disease phenotyping, risk prediction, and personalized precision care. The combination of data and information in a graph model to create knowledge graphs …
https://link.springer.com/article/10.1007/s10916-023-01951-2
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A Survey on Knowledge Graphs for Healthcare: …
(4 days ago) WebA healthcare knowledgegraph(HKG) is a domain-specific knowledge graph designed to capture medical concepts such as drugs, diseases, genes, phenotypes, and so on, and their relationships in a structured and semantic way. 2.2. HKG Construction Healthcare knowledge graphs can be constructed from scratch or through the integration of …
https://arxiv.org/pdf/2306.04802v1
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Introduction to Knowledge Graphs in Healthcare - Oracle …
(5 days ago) WebIntroduction to Knowledge Graphs in Healthcare. The healthcare industry is of utmost importance and focuses on the development of various systems that enable prolonged health through proper diagnoses, predictions, and treatments. Despite the drive to continually innovate and improve patient outcomes, the domain of healthcare services …
https://blogs.oracle.com/ai-and-datascience/post/introduction-to-knowledge-graphs-in-healthcare
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A Survey on Knowledge Graphs for Healthcare: Resources, …
(Just Now) WebA healthcare knowledge graph (HKG) is a domain-specific knowledge graph designed to capture medical concepts such as drugs, diseases, genes, phenotypes, and so on, and their relationships in a structured and semantic way. 2.2. HKG Construction Healthcare knowledge graphs can be constructed from
https://openreview.net/pdf?id=CZCktJoBRh
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Knowledge Graphs and Explainable AI in Healthcare
(8 days ago) WebKnowl-edge graphs can be used in XAI for explainability by structuring information, extracting features and relations, and performing reasoning. This paper highlights the role of knowledge graphs in XAI models in healthcare, considering a state-of-the-art review. Based on our review, knowledge graphs have been used for …
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Knowledge Graphs Can Move Healthcare into the Future
(9 days ago) WebIBM defines a knowledge graph (KG) as “a network of real-world entities—i.e. objects, events, situations, or concepts—and illustrates the relationship between them. This information is usually stored in a graph database and visualized as a graph structure, prompting the term knowledge graph.”. For many clinicians, that’s a …
https://www.mayoclinicplatform.org/2023/12/21/knowledge-graphs-can-move-healthcare-into-the-future/
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A very simple guide to Knowledge Graphs for Health Data Scientists
(9 days ago) Web(Image by author) The full knowledge graph after two inference computations. In knowledge graphs, we usually separate things into two groups: T-box and A-box(see the above two regions that are separated by the green dashed line). Anything about concepts and their relationships is part of the T-box, which stands for terminology …
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Automated Knowledge Graph Construction for Healthcare Domain
(2 days ago) WebAbstract. This research seeks to optimize the process of identifying correlations in common and high severity diseases via the fusion of knowledge graphs and deep learning artificial intelligence. Knowledge graphs can be complicated to construct and resource-intensive, alternatively, knowledge graphs can be seen to legitimize …
https://link.springer.com/chapter/10.1007/978-3-031-20627-6_24
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Knowledge Graphs and Explainable AI in Healthcare - MDPI
(Just Now) WebBuilding trust and transparency in healthcare can be achieved using eXplainable Artificial Intelligence (XAI), as it facilitates the decision-making process for healthcare professionals. Knowledge graphs can be used in XAI for explainability by structuring information, extracting features and relations, and performing reasoning. This …
https://www.mdpi.com/2078-2489/13/10/459
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Learning a Health Knowledge Graph from Electronic Medical Records
(3 days ago) WebGoogle health knowledge graph . A novel aspect of our study is the use of an expansive and manually curated health knowledge graph provided, with permission to use, by Google. The Google health knowledge graph, first announced in 2015, aims to empower users in their health decisions 19. Google created the graph using a multi-step …
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5519723/
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Healthcare Knowledge Graph Construction: State-of-the-art, …
(2 days ago) WebThe incorporation of data analytics in the healthcare industry has made significant progress, driven by the demand for efficient and effective big data analytics solutions. Knowledge graphs (KGs) have proven utility in this arena and are rooted in a number of healthcare applications to furnish better data representation and knowledge inference.
https://arxiv.org/pdf/2207.03771
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Constructing public health evidence knowledge graph for decision …
(7 days ago) WebWe release an COVID-19 public health evidence knowledge graph (CPHE-KG), which is an early exploration of KG applied to public health decision-making. 3) Our KG can provide two main functions: evidence querying and evidence mapping visualization, which has been proved to be effective in supporting decision-making relevant to COVID …
https://www.sciencedirect.com/science/article/pii/S266644962100030X
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[PDF] A Review on Knowledge Graphs for Healthcare: Resources
(6 days ago) WebThis work provides the first comprehensive review of HKGs, summarizes the pipeline and key techniques for HKG construction, as well as the common utilization approaches, i.e., model-free and model-based. Healthcare knowledge graphs (HKGs) are valuable tools for organizing biomedical concepts and their relationships with …
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Knowledge Graph Applications in Medical Imaging - Health …
(9 days ago) WebAmong all the included articles, the most common application of knowledge graphs in medical imaging is disease classification (56.5%), followed by disease localization and segmentation (17.4%), report generation (17.4%), and image retrieval (8.7%) (Figure 5 ). Figure 3 Year trend of reviewed articles. Open in viewer.
https://spj.science.org/doi/10.34133/2022/9841548
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A novel customizing knowledge graph evaluation method for
(Just Now) WebKnowledge graph quality assessment refers to the assessment of the triples in the knowledge graph in terms of accuracy, completeness, consistency, and redundancy 1,2,3,4,5.More specifically
https://www.nature.com/articles/s41598-024-60004-x
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[2306.04802] A Review on Knowledge Graphs for Healthcare: …
(2 days ago) WebA Review on Knowledge Graphs for Healthcare: Resources, Applications, and Promises. Healthcare knowledge graphs (HKGs) are valuable tools for organizing biomedical concepts and their relationships with interpretable structures. The recent advent of large language models (LLMs) has paved the way for building more comprehensive …
https://arxiv.org/abs/2306.04802
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Predicting Future Disorders via Temporal Knowledge Graphs and …
(1 days ago) WebDespite the vast potential for insights and value present in Electronic Health Records (EHRs), it is challenging to fully leverage all the available information, particularly that contained in the free-text data written by clinicians describing the health status of patients. Predicting Future Disorders via Temporal Knowledge Graphs and
https://pubmed.ncbi.nlm.nih.gov/38635388/
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arXiv:2306.04802v3 [cs.AI] 19 Feb 2024
(6 days ago) WebDefinition.A healthcare knowledge graph (HKG) is a domain-specific knowledge graph designed to capture medical concepts such as drugs, diseases, genes, phenotypes, and so on, and their relationships in a structured and semantic way. Terminology. Our focus is on healthcare knowledge graphs (HKGs), which are struc-
https://arxiv.org/pdf/2306.04802.pdf
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