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Qingjin Qian

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Open access Aug 2026

Machine learning quantifies immuno-virological interactions: a TRIPOD+AI compliant prediction model for HIV-1 salvage therapy outcomes

The developed XGBoost model overcomes the limitations of traditional linear scoring and achieves precise prediction of HIV salvage therapy outcomes by quantifying immune modulatory effects and therapeutic exhaustion markers.

De-Fu Yuan, Yang-Yang Liu, Shan-Shan Liu et al. · 0 citations

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