Configuration File Instructions

Below are the instructions to create a valid configuration file.

Configuration File Structure

The configuration file should be in YAML format (.config file) and follow the structure outlined below for ICU Data:

disease_label: <disease_label> mandatory only if the prediction task is Phenotype
timePrediction: <timePrediction>
timeWindow: <timeWindow>
timebucket: <timebucket>
radimp: <radimp>
predW: <predW>
diagnosis: <diagnosis>
output: <output>
chart: <chart>
proc: <proc>
meds: <meds>
disease_filter: <disease_filter>
icu_no_icu: <icu_no_icu>
groupingDiag: <groupingDiag>
select_diag: <select_diag>
select_med: <select_med>
select_proc: <select_proc>
select_out: <select_out>
select_chart: <select_chart>
outlier_removal: <outlier_removal>
outlier: <outlier>
left_outlier: <left_outlier>

The configuration file should be in YAML format (.config file) and follow the structure outlined below for Non-ICU Data:

disease_label: <disease_label> mandatory only if the prediction task is Phenotype
timePrediction: <timePrediction>
timeWindow: <timeWindow>
timebucket: <timebucket>
radimp: <radimp>
predW: <predW>
diagnosis: <diagnosis>
lab: <lab>
proc: <proc>
meds: <meds>
disease_filter: <disease_filter>
icu_no_icu: <icu_no_icu>
groupingDiag: <groupingDiag>
groupingProc: <groupingProc>
groupingMed: <groupingMed>
select_diag: <select_diag>
select_med: <select_med>
select_proc: <select_proc>
select_lab: <select_lab>
outlier_removal: <outlier_removal>
outlier: <outlier>
left_outlier: <left_outlier>

Replace the <variable> placeholders with the corresponding values specific to your use case. Detailed explanations of each variable and their valid values are provided in the next section.

Variable Definitions and Valid Values

disease_label (string): Specifies the disease label for Phenotype prediction task. Don't provide the line if the task is not Phenotype. Valid values: CAD, Heart Failure, CKD, COPD.
timePrediction (integer): Specifies the time prediction (days). Valid values depend on the task:
- For Phenotype task: 30
- For Mortality task: 0
- For Length of Stay task: Between 1 and 10 (inclusive)
- For Readmission task: Between 10 and 150 (inclusive), multiple of 10
timeWindow (string): Specifies the time window. Valid values:
- For Phenotype or Readmission task: Last X hours (with 24 <= X >= 72)
- For Mortality or Length of Stay tasks: First X hours (with 24 <= X >= 72)
timebucket (integer): Specifies the time bucket. Valid values: Between 1 and 6 (inclusive).
radimp (string): Specifies the imputation method. Valid values:
- No Imputation
- forward fill and mean
- forward fill and median
predW (integer): Specifies the prediction window. Valid values depend on the task:
- For Phenotype, Length of Stay, or Readmission tasks: 0
- For Mortality task: Between 2 and 8 (inclusive)
diagnosis, output, chart, proc, meds, lab (boolean): Specifies whether to include each respective feature. Valid values: True or False.
disease_filter (string): Specifies the disease filter if focusing on a cohort with a specific chronic disease. Valid values:
- Heart Failure
- COPD
- CKD
- CAD
- No Disease Filter
icu_no_icu (string): Specifies the dataset type. Valid values: ICU.
groupingDiag (string): Specifies the grouping ICD option for diagnosis. Valid values:
- Convert ICD-9 to ICD-10 and group ICD-10 codes
- Keep both ICD-9 and ICD-10 codes
- Convert ICD-9 to ICD-10 codes
groupingMed: Specifies if grouping Medication codes should be done to use Non propietary names : Valid values : Yes, No
groupingProc : Specifies the ICD codes version to perform grouping for procedures : Valid values :
- ICD-9 and ICD-10
- ICD-10
select_diag, select_med, select_proc, select_out, select_chart,select_lab (boolean): Specifies whether to do features selection as describe in https://github.com/healthylaife/MIMIC-IV-Data-Pipeline benchmark. Valid values: True or False.
outlier_removal (string): Specifies the outlier removal method. Valid values:
- No outlier detection
- Impute Outlier (default:98)
- Remove outliers (default:98)
outlier (integer): Specifies the outlier threshold. Valid values: Between 90 and 99 (inclusive).
left_outlier (integer): Specifies the left outlier threshold. Valid values: Between 0 and 10 (inclusive).

Example Configuration File

Here's an example of a valid configuration file for ICU Data:

disease_label: CAD
timePrediction: 30
timeWindow: Last 72 hours
timebucket: 2
radimp: forward fill and mean
predW: 0
diagnosis: True
output: True
chart: True
proc: True
meds: True
disease_filter: No Disease Filter
icu_no_icu: ICU
groupingICD: Convert ICD-9 to ICD-10 and group ICD-10 codes
select_diag: False
select_med: False
select_proc: False
select_out: False
select_chart: False
outlier_removal: Impute Outlier (default:98)
outlier: 98
left_outlier: 0

Here's an example of a valid configuration file for Non-ICU Data:

timePrediction: 0
timeWindow: First 48 hours
timebucket: 2
radimp: forward fill and mean
predW: 2
diagnosis: True
lab: True
proc: False
meds: False
disease_filter: CKD
icu_no_icu: ICU
groupingDiag: Convert ICD-9 to ICD-10 and group ICD-10 codes
select_diag: False
select_med: False
select_proc: False
select_lab: False
outlier_removal: Impute Outlier (default:98)
outlier: 98
left_outlier: 0
groupingMed: Yes
groupingProc: ICD-10

Feel free to modify the values to fit your specific requirements.

Usage

Provide the full path of your configuration file while calling the loading dataset function with the parameter config_path=<path_to_config_file>.

For more understanding of the configuration please refer to https://github.com/healthylaife/MIMIC-IV-Data-Pipeline.