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CDPMF-DDA: contrastive deep probabilistic matrix factorization for drug-disease association prediction
Published 2025-01-01“…Additionally, case studies on Alzheimer’s disease and epilepsy further validate the model’s effectiveness, demonstrating its high accuracy and robustness in drug-disease association prediction. Based on a multi-view contrastive learning framework, CDPMF-DDA is capable of integrating multi-source information and effectively capturing complex drug-disease associations, making it a powerful tool for drug repositioning and the discovery of new therapeutic strategies.…”
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Features first translation confucian text “Lunyu” on russian language
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Geochemical and hydrogeological parameters informativity in oil and gas geology
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