2 repository-uri
Utilities for transforming raw electronic health records into formats suitable for longitudinal analysis and machine learning.
Distinct from Clinical Documentation And EHR: Focuses on the processing and transformation of EHR data for research, whereas candidates focus on clinical documentation systems or AI agentic systems.
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This project is a research data sharing framework and provenance protocol designed to ensure computational reproducibility. It provides a standardized set of guidelines for transforming raw source data into tidy formats through documented processing scripts and cleaning workflows. The framework distinguishes itself by emphasizing a strict provenance-based packaging system. It requires the organization of raw data, processing recipes, and code books into a single package, ensuring that original unmodified sources are preserved to allow for independent verification of all transformation steps.
Provides a delivery format that preserves original sources and analysis context for clinical research.
mimic-code is a clinical data analysis framework and toolset for processing deidentified electronic health records and intensive care unit data. It provides a healthcare SQL query library and a processing tool to transform raw health records into formats suitable for longitudinal analysis and machine learning. The project features a medical research notebook environment that integrates with cloud-hosted datasets, allowing for remote querying and analysis. It includes a DICOM imaging pipeline to retrieve chest radiographs and link medical imaging with structured clinical metadata. The framewo
Provides a processing tool to transform raw electronic health records into formats suitable for longitudinal analysis and machine learning.