Practices and Trends of Machine Learning Application in Nanotoxicology.

ABSTRACT: Machine Learning (ML) techniques have been applied in the field of nanotoxicology with very encouraging results. Adverse effects of nanoforms are affected by multiple features described by theoretical descriptors, nano-specific measured properties, and experimental conditions. ML has been proven very helpful in this field in order to gain an insight into features effecting toxicity, predicting possible adverse effects as part of proactive risk analysis, and informing safe design. At this juncture, it is important to document and categorize the work that has been carried out. This study investigates and bookmarks ML methodologies used to predict nano (eco)-toxicological outcomes in nanotoxicology during the last decade. It provides a review of the sequenced steps involved in implementing an

SUBMITTER: Furxhi I 

PROVIDER: S-EPMC7023261 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature