Supplementary Materials for: Supervised signal detection for adverse drug reactions in medication dispensing data

Published: 21 Apr 2018 | Version 1 | DOI: 10.17632/rsmrsf7m7r.1

Description of this data

This file compares potential signals of adverse drug reactions (ADRs) detected by sequence symmetry analysis (SSA) and supervised gradient boosting classifier. ADR signals of higher confidence are assigned higher adjusted sequence ratios (rightward) by SSA and higher probabilities (upward) by gradient boosting classifier. Blue circles represent known ADRs while red squares indicate unknown potential ADR signals. A signal is picked up by SSA if the 95% confidence interval lower limit of its adjusted sequence ratio exceeds 1 and picked up by gradient boosting classifier if its probability is greater than 0.5. ADR signals of higher confidence are assigned higher adjusted sequence ratios (rightward) by SSA and higher probabilities (upward) by gradient boosting classifier.

Experiment data files

This data is associated with the following publication:

Supervised signal detection for adverse drug reactions in medication dispensing data

Published in: Computer Methods and Programs in Biomedicine

Latest version

  • Version 1

    2018-04-21

    Published: 2018-04-21

    DOI: 10.17632/rsmrsf7m7r.1

    Cite this dataset

    Hoang, Tao; Li, Jiuyong; Liu, Jixue; Pratt, Nicole; Roughead, Elizabeth (2018), “Supplementary Materials for: Supervised signal detection for adverse drug reactions in medication dispensing data”, Mendeley Data, v1 http://dx.doi.org/10.17632/rsmrsf7m7r.1

Categories

Data Mining, Drug Adverse Reactions, Machine Learning, Pharmacovigilance

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Licence

CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

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This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.

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