CarD-T: LLM Automated Literature Review for the Nomination & Analysis of Potential Human Carcinogens
CarD-T is an automated pipeline that combines transformer-based machine learning with probabilistic analysis to identify potential carcinogens from biomedical literature. The framework processes accumulating scientific publications, applies a trained Named Entity Recognition (NER) model to extract potential carcinogenic entities, and Probabilistic Carcinogen Denomination (or PCarD) to analyze temporal trends in evidence shifts. This approach enables classification of candidates through Bayesian temporal analysis, overcoming limitations of traditional manual literature review methods.
Authors
- Ludmil B. Alexandrov (ORCID: https://orcid.org/0000-0003-3596-4515)
- Jamey O’Neill (ORCID: https://orcid.org/0009-0001-8532-8405)
- Parag Katira
Institutions
- San Diego State University (US)
- University of California San Diego (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-29
- DOI
- https://doi.org/10.5281/zenodo.23781178
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00