Artificial intelligence in chemistry: current trends and future directions

ZJ Baum, X Yu, PY Ayala, Y Zhao… - Journal of Chemical …, 2021 - ACS Publications
The application of artificial intelligence (AI) to chemistry has grown tremendously in recent
years. In this Review, we studied the growth and distribution of AI-related chemistry …

Deep learning based regression and multiclass models for acute oral toxicity prediction with automatic chemical feature extraction

Y Xu, J Pei, L Lai - Journal of chemical information and modeling, 2017 - ACS Publications
Median lethal death, LD50, is a general indicator of compound acute oral toxicity (AOT).
Various in silico methods were developed for AOT prediction to reduce costs and time. In …

Chemometrics for selection, prediction, and classification of sustainable solutions for green chemistry—A review

M Bystrzanowska, M Tobiszewski - Symmetry, 2020 - mdpi.com
In this review, we present the applications of chemometric techniques for green and
sustainable chemistry. The techniques, such as cluster analysis, principal component …

QSPR estimation models of normal boiling point and relative liquid density of pure hydrocarbons using MLR and MLP-ANN methods

MR Fissa, Y Lahiouel, L Khaouane, S Hanini - Journal of Molecular …, 2019 - Elsevier
This work aimed to predict the normal boiling point temperature (Tb) and relative liquid
density (d20) of petroleum fractions and pure hydrocarbons, through a multi-layer …

New QSPR models for predicting critical temperature of binary organic mixtures using linear and nonlinear methods

Y Pan, F Yang, H Zhang, Y Yan, X Ping, M Yu… - Fluid Phase Equilibria, 2023 - Elsevier
The critical temperature is an important parameter in the design and selection of binary
organic mixtures. Rapid and accurate prediction has been a focus of research. Strong …

QSAR modeling in ecotoxicological risk assessment: application to the prediction of acute contact toxicity of pesticides on bees (Apis mellifera L.)

M Hamadache, O Benkortbi, S Hanini… - … Science and Pollution …, 2018 - Springer
Despite their indisputable importance around the world, the pesticides can be dangerous for
a range of species of ecological importance such as honeybees (Apis mellifera L.). Thus, a …

Electrochemical degradation of ciprofloxacin from water: Modeling and prediction using ANN and LSSVM

P Abbasi, EB Moghadam - Physics and Chemistry of the Earth, Parts A/B/C, 2023 - Elsevier
Ciprofloxacin is a widely used antibiotic that is also a persistent contamination that causes
major health and environmental risks. This study investigated the electrochemical removal of …

[PDF][PDF] Modeling and optimization of small-scale NF/RO seawater desalination using the artificial neural network (ANN)

A Adda, S Hanini, S Bezari, M Laidi… - Environmental Engineering …, 2022 - eeer.org
The performance of seawater hybrid NF/RO desalination plant including permeate
conductivity; permeate flow rate and permeate recovery. Under different feed parameters …

Prediction of the antibacterial activity of garlic extract on E. coli, S. aureus and B. subtilis by determining the diameter of the inhibition zones using artificial neural …

D Atsamnia, M Hamadache, S Hanini… - LWT-Food Science and …, 2017 - Elsevier
The aim of this study was to devise a model that predicts the inhibition zone diameter using
artificial neural networks. The concentration, temperature and the exposure time of our …

QSPR Modelling of the Solubility of Drug and Drug‐like Compounds in Supercritical Carbon Dioxide

I Euldji, C Si‐Moussa, M Hamadache… - Molecular …, 2022 - Wiley Online Library
Quantitative structure–property relationship (QSPR) modeling was investigated to predict
drug and drug‐like compounds solubility in supercritical carbon dioxide. A dataset of 148 …