2022/07/25 by Philip Darke, Darke, Philip, Paolo Missier +3
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Healthcare #Time Series Analysis and Forecasting
paper · pdf · doi:10.48550/arxiv.2207.12503
openalex publication_date 2022/07/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.