https://github.com/aqibsaeed/multilabel-timeseries-classification-with-lstm

Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.
https://github.com/aqibsaeed/multilabel-timeseries-classification-with-lstm

deep-learning lstm multi-label-classification tensorflow time-series

Last synced: 4 days ago
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Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.

• Host: GitHub
• URL: https://github.com/aqibsaeed/multilabel-timeseries-classification-with-lstm
• Owner: aqibsaeed
• License: apache-2.0
• Created: 2016-12-14T08:59:37.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2017-04-18T14:09:23.000Z (over 7 years ago)
• Last Synced: 2024-11-05T04:34:06.214Z (8 days ago)
• Topics: deep-learning, lstm, multi-label-classification, tensorflow, time-series
• Language: Jupyter Notebook
• Homepage:
• Size: 8.79 KB
• Stars: 573
• Watchers: 39
• Forks: 188
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
### Multilabel time series classification with LSTM

Tensorflow implementation of model discussed in the following paper: Learning to Diagnose with LSTM Recurrent Neural Networks.

### Tools Required

Python 3.5 is used during development and following libraries are required to run the code provided in the notebook:

* Tensorflow

* Numpy

* Pandas

### Dataset

Cleaned version of MIMIC-III dataset and accompanying paper


MIMIC-III dataset can possibly be use to train and test the model. Beware this is not the data set used by the authors of the paper.


Note: If you see mistakes, want to suggest changes or have dataset that can be use to train/test the model, please submit a pull request.