Unraveling the Complex Interactions: Machine Learning Approaches to Predict Bacterial Survival against ZnO and Lanthanum-Doped ZnO Nanoparticles

• Hauptverfasser: Diego E. Navarro-López (Verfasst von), Yocanxóchitl Perfecto-Avalos (Verfasst von), Araceli Zavala (Verfasst von), Marco A. de Luna (Verfasst von), Araceli Sanchez-Martinez (Verfasst von), Oscar Ceballos-Sanchez (Verfasst von), Naveen Tiwari (Verfasst von), Edgar R. López-Mena (Verfasst von), Gildardo Sanchez-Ante (Verfasst von)
• Format: Buch
• Veröffentlicht: MDPI AG, 2024-02-01T00:00:00Z.
• Schlagworte: article
• Online-Zugang: Connect to this object online.

The rise in antibiotic-resistant bacteria is a global health challenge. Due to their unique properties, metal oxide nanoparticles show promise in addressing this issue. However, optimizing these properties requires a deep understanding of complex interactions. This study incorporated data-driven mac...