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

• Ngā kaituhi matua: Diego E. Navarro-López (Author), Yocanxóchitl Perfecto-Avalos (Author), Araceli Zavala (Author), Marco A. de Luna (Author), Araceli Sanchez-Martinez (Author), Oscar Ceballos-Sanchez (Author), Naveen Tiwari (Author), Edgar R. López-Mena (Author), Gildardo Sanchez-Ante (Author)
• Hōputu: Pukapuka
• I whakaputaina: MDPI AG, 2024-02-01T00:00:00Z.
• Ngā marau: article
• Urunga tuihono: 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...