Shypd.aiThe largest open index of AI toolsMultilabel-timeseries-classification-with-LSTM is an open-source tool that provides a TensorFlow implementation for multilabel time series classification. It is based on the paper "Learning to Diagnose with LSTM Recurrent Neural Networks."
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Multilabel-timeseries-classification-with-LSTM offers a TensorFlow implementation for performing multilabel time series classification, drawing inspiration from the research paper "Learning to Diagnose with LSTM Recurrent Neural Networks." This open-source project is designed for developers and researchers working with time series data and deep learning models. It requires Python 3.5, along with the essential libraries TensorFlow, NumPy, and Pandas for its operation. The tool is noted to be compatible with a cleaned version of the MIMIC-III dataset, although it's important to note that this is not the original dataset used by the paper's authors. Users are encouraged to contribute through pull requests for improvements, suggestions, or to provide alternative datasets for training and testing the model.
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