Here stores code for understanding MIMIC data.
mimic101.md gives detailed documentations on how MIMIC database (not demo) is created, in addition to some exploratory understandings on the tables.
mimic101.sql gives some initial attemps using sql.
mimic101.R connects the database with R, try to query from R, and does some exploratory plots.
postgres_create_tables.sql creates tables in postgresql database.
postgres_load_data.sql loads data (unzipped) into postgresql tables created by above.
postgres_load_data_mycode.sql loads data (zipped) into tables created by above. This is useful when I don't want to unzip or it's too time consuming to unzip.
cohortPartitionT.sql (not used) attempts to partition tables. This method is not used because it requires partitions by heritance to be set up before loading data.
cohortPartititonM.R creates 50 quantiles for patient ID (subject_id). Used for partitioning large chartevents for performance.
cohortPartitionM.sql partitions table chartevents into 50 intervals into materialized views, with names ce_1, …, ce_50.
table information: A list of variables and data types for tables in MIMIC database.
variable_index_carevue: as the name suggests.
The other csvs: more detailed indices related to some variables.
Subject_id, hadm_id, icustay_id tables for a selected cohort, for project 2. Detailed information see Project 2.
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sepsisDeadApr18.csvfor patients who are eventually dead. -
sepsisUndeadApr18.csv
Not used for now.
Information related to signal data in MIMIC database.
Definition of diagnosis, used by Harutyunyan 2018 paper.
Information related to Harutyunyan 2018 benchmark paper. This paper is useful for comparing methods used on MIMIC dataset.
Angus criteria of sepsis.