  The development of models for Electronic Health Record data is an area of
active research featuring a small number of public benchmark data sets.
Researchers typically write custom data processing code but this hinders
reproducibility and can introduce errors. The Python package torchtime provides
reproducible implementations of commonly used PhysioNet and UEA & UCR time
series classification repository data sets for PyTorch. Features are provided
for working with irregularly sampled and partially observed time series of
unequal length. It aims to simplify access to PhysioNet data and enable fair
comparisons of models in this exciting area of research.
