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Pretrained Medical Representations for the Practical Screening of Drug Repositioning Candidates

arXiv · AI, language, vision and robotics · article · Sep 17, 2026 · UTC

Representation learning from medical code sequences in electronic health records and medical claims data has been successful in various clinical applications, such as those regarding disease prediction. However, significant challenges remain in extending this approach to the discovery of scientific hypotheses. One reason is that many existing BERT-based models fail to adequately capture the hierarchical structure of medical codes and the complex interactions between diagnoses and treatments. To address these limitations, we propose a new unified pre-training framework that explicitly integrate

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