Recently, research on the development of artificial intelligence (AI)-based computational toxicology models that predict toxicity without the use of animal testing has emerged …
AV Singh, M Varma, M Rai… - Advanced Intelligent …, 2024 - Wiley Online Library
The escalating use of novel chemicals and nanomaterials (NMs) across diverse sectors underscores the need for advanced risk assessment methods to safeguard human health …
Y Abdalla, M Elbadawi, M Ji, M Alkahtani… - International Journal of …, 2023 - Elsevier
Abstract Three-dimensional (3D) printing is drastically redefining medicine production, offering digital precision and personalized design opportunities. One emerging 3D printing …
This study focuses on the development of a machine learning ensemble approach for the classification of Beta-Secretase 1 (BACE1) inhibitors in Quantitative Structure-Activity …
SK Niazi, Z Mariam - International Journal of Molecular Sciences, 2023 - mdpi.com
In modern drug discovery, the combination of chemoinformatics and quantitative structure– activity relationship (QSAR) modeling has emerged as a formidable alliance, enabling …
This study aimed to provide insights into the risk posed by psychopharmaceuticals and illicit drugs in European surface waters, and to identify current knowledge gaps hampering this …
The prediction of compound properties from chemical structure is a main task for machine learning (ML) in medicinal chemistry. ML is often applied to large data sets in applications …
S Xu, X Xu, C Blacker, R Gaulton, Q Zhu, M Yang… - Remote Sensing, 2023 - mdpi.com
LNC (leaf nitrogen content) in crops is significant for diagnosing the crop growth status and guiding fertilization decisions. Currently, UAV (unmanned aerial vehicles) remote sensing …
Fungal infections or mycosis cause a wide range of diseases in humans and animals. The incidences of community acquired; nosocomial fungal infections have increased …