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                <identifier>oai:data.mendeley.com/3ztcsxvjyb.1</identifier>
                <datestamp>2025-07-23T15:05:04Z</datestamp>
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    <dc:creator id="https://orcid.org/0009-0006-1069-3738">Vergara Roa, Mateo</dc:creator>
    <dc:title>Artificial Neural Network Modeling of Drug Solubility in Cosolvent Systems</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>This notebook implements an artificial neural network (ANN) to predict drug solubility in cosolvent systems. It includes data preprocessing, model architecture definition, training, and performance evaluation using regression metrics. The goal is to explore the non-linear relationships between solubility and experimental variables such as temperature and cosolvent composition.</dc:description>
    <dc:subject>Computer Science</dc:subject>
    <dc:subject>Chemistry</dc:subject>
    <dc:subject>Artificial Neural Network</dc:subject>
    <dc:subject>Data Science</dc:subject>
    <dc:subject>Machine Learning</dc:subject>
    <dc:subject>Applied Computer Science</dc:subject>
    <dc:contributor id="https://orcid.org/0000-0003-4601-0602">Cardenas Torres, Rossember Edén</dc:contributor>
    <dc:contributor id="https://orcid.org/0000-0002-4835-9739">Delgado, Daniel Ricardo</dc:contributor>
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    <dc:identifier>doi:10.17632/3ztcsxvjyb.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/3ztcsxvjyb.1</dc:identifier>
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    <dc:date>2025-07-23T15:05:04Z</dc:date>
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