Last updated: June 29,2023
We have created and implemented various ontology for health informatics usage.
Alzheimer's Disease Ontology
We have built some AD/ADRD related ontologies and knowledge base including Drug Repurposing-oriented Alzheimer's Disease Ontology (DROADO), Dementia-Related Agitation Non-Pharmacological Treatment Ontology (DRANPTO), and ADCareOnto - an ontology for personalized home care for persons with Alzheimer's disease.
CNTRO (Clinical Narrative Temporal Relation Ontology) allows temporal information of clinical data to be semantically annotated and queried, and use inference to expose new temporal features and relations based on the semantic assertions and definitions of the temporal aspects in the ontology.
Time Event Ontology (TEO) has been developed in order to provide a formal conceptualization of temporal structures in both structured data and textual narratives. To download, click on TEO.
Social Determinants of Health ontology (SDoHO) has been developed to comprehensively represent the concepts, hierarchies, and relations pertinent to SDoH factors. The standardization characteristics of ontology with the comprehensive representation of SDoH are intended to address the current challenge of heterogeneity. By ensuring semantic interoperability and data FAIRness, which means data is Findable, Accessible, Interoperable, and Reusable, our proposed ontology can be applicable to downstream applications, such as natural language processing (NLP), and further help with the clinical decision.
SDoHO is shaped for clinical medicine, public health, and biomedical informatics usages, acilitating systematic SDoH knowledge representation, integration, and reasoning.
To download, click on Social Determinants of Health ontology (SDoHO).
License: Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) https://creativecommons.org/licenses/by-nc/3.0/
Knowledge graphs are used to organize structured knowledge in the world. They are constructed from multiple data sources through information extraction. Knowledge graphs play a growing important role in the field of health data science and artificial intelligence.
The BDSI lab is interested in applying knowledge graphs in a variety of areas: ontology engineering for s ocial determinants of health, drug repurposing through natural language processing, and disease prediction with graph neural networks.
CNTRO TimeLine API: The CNTRO Timeline library is a Java library. This library is intended to be used by developer and analysts who want to integrate this library in their workspace to compute temporal information about clinical events. For more details, visit Timeline API Library.
All listed work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License. You should have received a copy of the license along with this work. If not, see http://creativecommons.org/licenses/by-sa/3.0/
For question regarding the usage of technologies and products in this page, please contact: BSDI@uth.tmc.edu