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.

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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
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article

CarD-T: LLM Automated Literature Review for the Nomination & Analysis of Potential Human Carcinogens

Ludmil B. Alexandrov, Jamey O’Neill, Parag Katira
3 links
Zenodo (CERN European Organization for Nuclear Research)
Biomedical Text Mining and Ontologies
article

CarD-T: LLM Automated Literature Review for the Nomination & Analysis of Potential Human Carcinogens

Ludmil B. Alexandrov, Jamey O’Neill, Parag Katira
article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
San Diego State University (US), University of California San Diego (US)
Good health and well-being
Openalex Percentile: Top 23%
Biomedical Text Mining and Ontologies
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