Knowledge4COVID-19: A semantic-based approach for constructing a COVID-19 related knowledge graph from various sources and analyzing treatments' toxicities
In this paper, we present Knowledge4COVID-19, a framework that aims to showcase the
power of integrating disparate sources of knowledge to discover adverse drug effects …
power of integrating disparate sources of knowledge to discover adverse drug effects …
Data ecosystems: sovereign data exchange among organizations (Dagstuhl Seminar 19391)
This report documents the program and the outcomes of Dagstuhl Seminar 19391``Data
Ecosystems: Sovereign Data Exchange among Organizations''. The goal of the seminar was …
Ecosystems: Sovereign Data Exchange among Organizations''. The goal of the seminar was …
Scaling up knowledge graph creation to large and heterogeneous data sources
RDF knowledge graphs (KG) are powerful data structures to represent factual statements
created from heterogeneous data sources. KG creation is laborious and demands data …
created from heterogeneous data sources. KG creation is laborious and demands data …
A neuro-symbolic system over knowledge graphs for link prediction
Neuro-Symbolic Artificial Intelligence (AI) focuses on integrating symbolic and sub-symbolic
systems to enhance the performance and explainability of predictive models. Symbolic and …
systems to enhance the performance and explainability of predictive models. Symbolic and …
Orffm: An ontology-based semantic model of river flow and flood mitigation
The provision of the heterogeneous information acquisition and managing of emerging
technologies with IoT, cloud-based storage, and improved communication services have …
technologies with IoT, cloud-based storage, and improved communication services have …
Knowledge graphs for enhancing transparency in health data ecosystems 1
Tailoring personalized treatments demands the analysis of a patient's characteristics, which
may be scattered over a wide variety of sources. These features include family history, life …
may be scattered over a wide variety of sources. These features include family history, life …
[HTML][HTML] Family history of cancer and lung cancer: Utility of big data and artificial intelligence for exploring the role of genetic risk
V Calvo, E Niazmand, E Carcereny… - Lung Cancer, 2024 - Elsevier
Abstract Objectives Lung Cancer (LC) is a multifactorial disease for which the role of genetic
susceptibility has become increasingly relevant. Our aim was to use artificial intelligence (AI) …
susceptibility has become increasingly relevant. Our aim was to use artificial intelligence (AI) …
What are the parameters that affect the construction of a knowledge graph?
A large number of datasets are made publicly available on a wide range of formats. Due to
interoperability problems, the construction of RDF-based knowledge graphs (KG) using …
interoperability problems, the construction of RDF-based knowledge graphs (KG) using …
Toward representing research contributions in scholarly knowledge graphs using knowledge graph cells
There is currently a gap between the natural language expression of scholarly publications
and their structured semantic content modeling to enable intelligent content search. With the …
and their structured semantic content modeling to enable intelligent content search. With the …
Eablock: A declarative entity alignment block for knowledge graph creation pipelines
Despite encoding enormous amount of rich and valuable data, existing data sources are
mostly created independently, being a significant challenge to their integration. Mapping …
mostly created independently, being a significant challenge to their integration. Mapping …