A formal explanation space for the simultaneous clustering of neurologic diseases based on their signs and symptoms
Clustering complex biomedical data often produces multiple biologically plausible solutions. Retaining and comparing such solutions within a formal explanation space enhances interpretability and supports the discovery of complementary insights across methods.
Authors
- Tayo Obafemi-Ajayi (ORCID: https://orcid.org/0000-0002-0155-9733)
- Michael D. Carrithers (ORCID: https://orcid.org/0000-0001-5337-0804)
- Daniel B. Hier (ORCID: https://orcid.org/0000-0002-6179-0793)
- Raghu Yelugam (ORCID: https://orcid.org/0000-0002-5821-244X)
- Donald C. Wunsch (ORCID: https://orcid.org/0000-0001-6800-1462)
Institutions
- Missouri State University (US)
- Missouri University of Science and Technology (US)
- University of Illinois Chicago (US)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-12-08
- DOI
- https://doi.org/10.1186/s12911-025-03297-w
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00