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Performance Validation of Neural Network Based 13 C NMR Prediction Using a Publicly Available Data Source

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What this work says

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

inferredcites →https://doi.org/10.1006/jmre.2002.2599openalex-snapshot
Using Neural Networks for 13C NMR Chemical Shift Prediction–Comparison with Traditional Methods
inferredcites →https://doi.org/10.1007/978-3-662-10207-7openalex-snapshot
Tables of Spectral Data for Structure Determination of Organic Compounds
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Computational NMR spectroscopy: reversing the information flow
inferredcites →https://doi.org/10.1016/0169-7439(93)80105-qopenalex-snapshot
The CSEARCH-NMR data base approach to solve frequent questions concerning substituent effects on 13C NMR chemical shifts
inferredcites →https://doi.org/10.1016/j.phytochem.2004.08.027openalex-snapshot
NMRShiftDB – compound identification and structure elucidation support through a free community-built web database
inferredcites →https://doi.org/10.1016/s0003-2670(00)85105-3openalex-snapshot
A computer program for the prediction of 13-C-NMR chemical shifts of organic compounds
inferredcites →https://doi.org/10.1016/s0003-2670(01)83100-7openalex-snapshot
Hose — a novel substructure code
inferredcites →https://doi.org/10.1021/ci000021copenalex-snapshot
Fast Determination of 13 C NMR Chemical Shifts Using Artificial Neural Networks
inferredcites →https://doi.org/10.1021/ci00010a023openalex-snapshot
Application of recurrent neural networks in chemistry. Prediction and classification of carbon-13 NMR chemical shifts in a series of monosubstituted benzenes
inferredcites →https://doi.org/10.1021/ci0341060openalex-snapshot
Structure Elucidator: A Versatile Expert System for Molecular Structure Elucidation from 1D and 2D NMR Data and Molecular Fragments
inferredcites →https://doi.org/10.1021/ci050469jopenalex-snapshot
Are Deterministic Expert Systems for Computer-Assisted Structure Elucidation Obsolete?
inferredcites →https://doi.org/10.1021/ci700256nopenalex-snapshot
Toward More Reliable 13C and 1H Chemical Shift Prediction: A Systematic Comparison of Neural-Network and Least-Squares Regression Based Approaches
inferredcites →https://doi.org/10.1021/ci950262yopenalex-snapshot
Computer Assisted Simulation of 13C Nuclear Magnetic Spectra of Monosaccharides
inferredcites →https://doi.org/10.1021/ja01069a005openalex-snapshot
Nuclear Magnetic Resonance Studies of Hydrogen Bonding. II. Calculation of the Shift upon Complex Formation
inferredcites →https://doi.org/10.1021/ol0611346openalex-snapshot
Predicting NMR Spectra by Computational Methods: Structure Revision of Hexacyclinol

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Nuclear Magnetic Resonance Spectroscopy
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The application of empirical methods of 13 C NMR chemical shift prediction as a filter for determining possible relative stereochemistry
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Empirical and DFT GIAO quantum‐mechanical methods of 13C chemical shifts prediction: competitors or collaborators?
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Predictive Modeling of NMR Chemical Shifts without Using Atomic-Level Annotations
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A Very Deep Graph Convolutional Network for13C NMR Chemical Shift Calculations with Density Functional Theory Level Performance for Structure Assignment
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Solubility Prediction from Molecular Properties and Analytical Data Using an In-phase Deep Neural Network (Ip-DNN)
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Chemical shifts in molecular solids by machine learning
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Predicting Solid-state NMR Observables via Machine Learning
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Structural revisions of natural products by Computer-Assisted Structure Elucidation (CASE) systems
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Real-time prediction of 1 H and 13 C chemical shifts with DFT accuracy using a 3D graph neural network
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A ubiquitous tire rubber–derived chemical induces acute mortality in coho salmon
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Can Graph Machines Accurately Estimate 13C NMR Chemical Shifts of Benzenic Compounds?
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