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Interpreting Computational Neural Network Quantitative Structure−Activity Relationship Models: A Detailed Interpretation of the Weights and Biases

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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/jps.2600760325openalex-snapshot
Molecular Connectivity in Structure–activity Analysis
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International Conference
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Highly discriminating distance-based topological index
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Integrating artificial neural networks with rule-based expert systems
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Molecular Connectivity in Chemistry and Drug Research
inferredcites →https://doi.org/10.1016/s0045-6535(02)00114-5openalex-snapshot
Quantitative structure–activity relationships (QSARs) for the prediction of skin permeation of exogenous chemicals
inferredcites →https://doi.org/10.1021/ac00220a013openalex-snapshot
Development and use of charged partial surface area structural descriptors in computer-assisted quantitative structure-property relationship studies
inferredcites →https://doi.org/10.1021/ci00023a011openalex-snapshot
Automated Descriptor Selection for Quantitative Structure-Activity Relationships Using Generalized Simulated Annealing
inferredcites →https://doi.org/10.1021/ci00043a009openalex-snapshot
On molecular identification numbers
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On the Physical Interpretation of QSAR Models
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Heuristic Extraction of Rules in Pruned Artificial Neural Networks Models Used for Quantifying Highly Overlapping Chromatographic Peaks
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Interpreting Computational Neural Network QSAR Models: A Measure of Descriptor Importance
inferredcites →https://doi.org/10.1021/ci9903049openalex-snapshot
Analysis of a Large Structure/Biological Activity Data Set Using Recursive Partitioning
inferredcites →https://doi.org/10.1063/1.1699114openalex-snapshot
Equation of State Calculations by Fast Computing Machines
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Rule generation from neural networks
inferredcites →https://doi.org/10.1109/69.824621openalex-snapshot
Generalized Analytic Rule Extraction for feedforward neural networks
inferredcites →https://doi.org/10.1109/72.977279openalex-snapshot
Interpretation of artificial neural networks by means of fuzzy rules
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History of Quantitative Structure–Activity Relationships
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Calculated Molecular Properties and Multivariate Statistical Analysis
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Interpreting Computational Neural Network Quantitative Structure—Activity Relationship Models: A Detailed Interpretation of the Weights and Biases.
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