Can Ai Revolutionize Qspr Models for the Chemical Mixtures Hazards?
The physical hazards of chemical mixtures are typically characterized using experimental tools that could benefit to be prioritized by using predictive methods.
Guillaume Fayet +2 more
doaj
Predictive modeling for physicochemical properties of β-lactam antibiotics through eigenvalue based topological indices and non linear regression techniques. [PDF]
Yuvaraj A +4 more
europepmc +1 more source
Interpreting Molecular Descriptors for Glass Transition Temperature Prediction and Design of Polyimides. [PDF]
Cui T, Liu H, Liu X, Min Y.
europepmc +1 more source
CORAL: the prediction of biodegradation of organic compounds with optimal SMILES-based descriptors
Toropov Andrey +6 more
doaj +1 more source
Developing a QSPR model for Alzheimer's drugs using topological indices and M-polynomial: A computational study. [PDF]
Akhbari MH +3 more
europepmc +1 more source
Predictive topological modeling of the structure-property relationships in naturally occurring anti-cancer chalcones. [PDF]
Obaid AAR +6 more
europepmc +1 more source
Leveraging topological indices and machine learning for advanced prediction of antidepressant drug properties. [PDF]
Zhang G +6 more
europepmc +1 more source
Applications of Sombor topological indices and entropy measures for QSPR modeling of anticancer drugs: a Python-based methodology. [PDF]
Kara Y +3 more
europepmc +1 more source
Correction to Retracted Article: Novel hybrid QSPR-GPR approach for modeling of carbon dioxide capture using deep eutectic solvents. [PDF]
Salahshoori I, Baghban A.
europepmc +1 more source
Novel temperature-based spectral topological indices for QSPR modeling of polyacenes in predicting physicochemical properties. [PDF]
Hayat S, Alanazi SJF, Belay MB, Wang S.
europepmc +1 more source

