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Construction and Validation of a Predictive Model for Voriconazole Treatment Efficacy in Influenza-Associated Pulmonary Aspergillosis Based on Machine Learning.
Clinical evidence update from Drug design, development and therapy
Clinical Context Peer-reviewed veterinary literature continues to shape everyday decision-making for production animal practice, especially when new evidence clarifies diagnosis, treatment selection, monitoring, or clinical outcomes.
What the Study Evaluated A study published in Drug design, development and therapy in 2026 evaluated construction and Validation of a Predictive Model for Voriconazole Treatment Efficacy in Influenza-Associated Pulmonary Aspergillosis Based on Machine Learning..
Key Findings To analyze risk factors affecting voriconazole efficacy in influenza-associated pulmonary aspergillosis (IAPA) and build interpretable machine learning (ML) predictive models. This retrospective study enrolled voriconazole-treated IAPA patients into a primary retrospective set (Jan 1, 2020-Jul 31, 2025) and a separate temporal external validation set (Aug 1, 2025-Apr 30, 2026). To av…
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