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Reverse Item Response Theory for Sparsity-Robust Ranking in Fragmented Cancer Drug-Response Matrices
Not provided in the abstract
pharmacogenomicsdrug-responserankingsparsity
2610.00002
Builder Relevance
20h ago70%
Abstract
The paper introduces a novel approach using reverse Item Response Theory to improve drug-response analysis in cancer treatment.
Reality Card
Core Claim
Reverse IRT outperforms simple averaging in recovering latent rankings of drug sensitivity in cancer types, particularly under conditions of data sparsity.
Method / Result
Achieved a Delta-rho improvement of +0.089 to +0.095 at 60% missingness across various sparsity regimes.
Limitations
The study indicates weak rank-order correlation in cross-platform validation, suggesting methodological robustness rather than a definitive clinical ranking.
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