The global cost-benefit analysis of pesticide use during the last 30 years has been
characterized by a significant increase during the period from 1990 to 2007 followed by a …

Ocular drug delivery presents a unique set of challenges owing to the complex anatomy and
physiology of the eye. Processed excipients have emerged as crucial components in …

The use of machine learning for predicting ecotoxicological outcomes is promising, but
underutilized. The curation of data with informative features requires both expertise in …

This study presents a novel approach to identifying trolls and toxic content on social media
using deep learning. We developed a machine-learning model capable of detecting toxic …

Imputation machine learning (ML) surpasses traditional approaches in modeling toxicity
data. The method was tested on an open-source data set comprising approximately 2500 …

Pesticides are recognized as common environmental contaminants. The potential pesticide
hazard to non-target organisms, including various mammal species, is a global concern. The …

Regulation of chemicals requires knowledge of their toxicological effects on a large number
of species, which has traditionally been acquired through in vivo testing. The recent effort to …

Abstract Quantitative Structure Activity Relation (QSAR) models are mathematical
techniques used to link structural characteristics with biological activities, thus considered a …

Although uncertainties expressed in texts within QSAR studies can guide quantitative
uncertainty estimations, they are often overlooked during uncertainty analysis. Using …

Valproic acid (VPA) is a primary medication for epilepsy, yet its hepatotoxicity consistently
raises concerns among individuals. This study aims to establish an automated machine …