RIDDLE
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About
RIDDLE is an open-source library developed in Python2 for imputing race and ethnicity information in anonymized electronic medical records (EMRs) by employing deep learning techniques. It is designed to work with large, high-dimensional datasets, allowing the building of models that estimate race and ethnicity based on clinical features. The library facilitates efficient model training through a parallelized TensorFlow-under-Keras backend and supports various neural network architectures (e.g., MLP, LSTM, CNN). The implementation leverages methods introduced in the PLOS Computational Biology paper from 2018, making it a robust tool for researchers needing to interpret how specific features contribute to predictions regarding demographic information in healthcare datasets.
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Task
Features
• open-source python library
• provides model interpretation via feature contribution scores
• handles large and high-dimensional datasets
• parallelized tensorflow-under-keras backend
• supports deep learning architectures
• imputes race and ethnicity in emrs
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