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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.

Platform

Keywords

deep learning medical records python library race and ethnicity data imputation

Task

data imputation

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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