Skip to content

For paper “Chemical-induced Disease Extraction via Convolutional Neural Networks ”

Notifications You must be signed in to change notification settings

wglassly/CID_ATTCNN

Repository files navigation


System Requrement:

python 2.7, theano, keras, gensim

sklearn     #for load KB features*

maybe acquired: h5py, libshortexts


How to use

  1. We have extracted all (cheimcal,disease) pairs from BiocreativeV CDR data and stored them in "data/" such as "train_full" . Knowledge-Bases features ("*.svm") also store in that folder.

      "train_full" and "test_full": full sentences

      "train_only_between" and "test_only_between": segment between two entities.

  2. Run:

    Test our model with KB features:

  python pos_fea_cnn.py data/train_full data/test_full
Test our model without KB features: 

python pos_cnn.py data/train_full data/test_full

Trainditional CNN model with KB features: 

python standard_fea_cnn.py data/train_only_between data/test_only_between

Trainditional CNN model without KB features: 
  python standard_cnn.py data/train_only_between data/test_only_between

Any questions pls connect [email protected]

About

For paper “Chemical-induced Disease Extraction via Convolutional Neural Networks ”

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages