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

• Hoofdauteurs: Diego E. Navarro-López (Auteur), Yocanxóchitl Perfecto-Avalos (Auteur), Araceli Zavala (Auteur), Marco A. de Luna (Auteur), Araceli Sanchez-Martinez (Auteur), Oscar Ceballos-Sanchez (Auteur), Naveen Tiwari (Auteur), Edgar R. López-Mena (Auteur), Gildardo Sanchez-Ante (Auteur)
• Formaat: Boek
• Gepubliceerd in: MDPI AG, 2024-02-01T00:00:00Z.
• Onderwerpen: article
• Online toegang: 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...