Correction: Predicting small molecules solubility on endpoint devices using deep ensemble neural networks
Mayk Caldas Ramos, Andrew D. White

TL;DR
This paper corrects a prior study on predicting small molecule solubility using deep learning models on endpoint devices.
Contribution
The paper provides corrections to the original study's content or presentation.
Findings
The original study's details or conclusions were found to require correction.
The corrections ensure accuracy and clarity in the reported methods and results.
Abstract
Correction for ‘Predicting small molecules solubility on endpoint devices using deep ensemble neural networks’ by Mayk Caldas Ramos and Andrew D. White, Digital Discovery, 2024, 3, 786–795, https://doi.org/10.1039/D3DD00217A.
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
- —National Institute of General Medical Sciences10.13039/100000057
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Taxonomy
TopicsComputational Drug Discovery Methods · Machine Learning in Materials Science · Analytical Chemistry and Chromatography
The reference list from the paper itself. Each links out to its DOI / PubMed record.
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