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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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O’Neill et al. (2026) studied this question.
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