NEMSIS Dataset
This project aims to evaluate various data imputation methods using Emergency Medical Services (EMS) data from the National Emergency Medical Services Information System (NEMSIS), focusing on MICE and MissForest, to identify predictors of ICU cardiac arrest outcomes, particularly with respect to urban versus rural settings.
Dataset description and usage context
Dataset Overview
Dataset Name
Imputation of NEMSIS Dataset for Cardiac Arrest Analysis
Dataset Purpose
The project aims to fill gaps in the National Emergency Medical Services Information System (NEMSIS) data to discover predictors of cardiac arrest outcomes in ICU patients, especially predicting based on urban versus rural settings.
Dataset Content
- data
- ASCII_2020
- processeddataCA.zip: EMS data from NEMSIS.
- filtered_data: Dataset processed by scripts.
- Imputed_Data_MICE: Dataset imputed using the MICE method.
- Imputed_Data_MICE&MissForest: Dataset imputed using both MICE and Miss Forest methods.
- fig: Figures used in project analysis.
- reference: NEMSIS data dictionary, case definitions, and other related materials.
- ASCII_2020
Dataset Source
- Original data source: NEMSIS Database
- Subset of data obtainable from scientists at the Roux Institute:
- Filename: "processeddataCA.zip"
- Size: 55,649,704 bytes
Dataset Usage
- Create a reproducible environment using Miniconda or Anaconda.
Pair the dataset with AI analysis and content workflows.
Once the source passes your review, move straight into summarization, transformation, report drafting, or presentation generation with the JuheAI toolchain.