Three-layered semantic framework for public health intelligence
The framework showcased its capability to address intricate, multi-domain queries and support diverse levels of detail. Additionally, it demonstrated proficiency in data analysis and visualization, generating graphs that depict patterns and trends; however, challenges related to ontology maintenance, alignment, and mapping must be addressed for the approach's optimal utilization.
Authors
- Alpha Tom Kodamullil (ORCID: https://orcid.org/0000-0001-9896-3531)
- Martin Hofmann‐Apitius (ORCID: https://orcid.org/0000-0001-9012-6720)
- Abish Kaladharan
- Bide Zhang (ORCID: https://orcid.org/0000-0002-6571-0033)
- Astghik Sargsyan (ORCID: https://orcid.org/0000-0002-5860-6369)
- Marc Jacobs (ORCID: https://orcid.org/0000-0003-4153-3930)
- Priya Sethumadhavan (ORCID: https://orcid.org/0000-0002-4983-6728)
- Sathvik Guru Rao (ORCID: https://orcid.org/0009-0005-1836-6021)
- Pranitha Rokkam
Institutions
- University of Bonn (DE)
- Cochin University of Science and Technology (IN)
- Fraunhofer Institute for Algorithms and Scientific Computing (DE)
- Bonn Aachen International Center for Information Technology (DE)
Publication Details
- Journal
- Journal of Biomedical Semantics
- Published
- 2025-09-15
- DOI
- https://doi.org/10.1186/s13326-025-00338-1
- Citations
- 1
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.81