Multichannel CNN Model to support Citation Screening in the Systematic Literature Review Process

To run this code, please upload it to Google Colab. Also, make sure you download the 100-dimensional GloVe embeddings trained on 6B words from https://nlp.stanford.edu/projects/glove/

The SWIFT review datasets can be retrieved from Howard, B.E., Phillips, J., Miller, K. et al. SWIFT-Review: a text-mining workbench for systematic review. Syst Rev 5, 87 (2016). https://doi.org/10.1186/s13643-016-0263-z The drug review datasets can be retrieved from Cohen AM, Hersh WR, Peterson K, Yen PY. Reducing Workload in Systematic Review Preparation Using Automated Citation Classification. JAMIA 2006: https://dmice.ohsu.edu/cohenaa/systematic-drug-class-review-data.html

Please download the datasets and develop your own script using Entrez (https://biopython.org/docs/1.75/api/Bio.Entrez.html) to obtain title and abstracts. Some articles do not contain an abstract, as they are interviews or book chapters.

Citing this code

For citing this code, please refer to van Dinter, R., Catal, C., & Tekinerdogan, B. (2021). A Multi-Channel Convolutional Neural Network approach to automate the citation screening process. Applied Soft Computing, 112, 107765.