Author

Suparno Roy Chowdhury

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#artificial intelligence Review Oct 2026

Answering clinicians'questions over trial evidence tables with verifiable, feedback-driven language models

Systematic reviews condense clinical trials into evidence tables, yet clinicians can interrogate these tables only through database queries, and many questions concern attributes that the table does not record, such as a drug's target class or a harmonised endpoint. Here we introduce FD-SCoPE, a language-model framewor...

M. Choudhury, Suparno Roy Chowdhury, S. Sahoo et al. · 0 citations

#artificial intelligence Preprint Sep 2026

CIPHER: Benchmarking Cross-record Inference over Privacy-Hardened Evidence Records

This work introduces CIPHER (Cross-record Inference over Privacy-Hardened Evidence Records), a benchmark of expert-validated questions from consumer-finance, clinical, and law-enforcement records that evaluate retrieval, prompting, table-specialist, and hybrid symbolic-neural systems under native redaction and surrogat...

Suparno Roy Chowdhury, M. Choudhury, Dhruv Madhwal et al. · 0 citations