Comments (1)
mehak25
commented on August 15, 2024
Our strategy for extracting disease-specific cohorts is as follows:
- We first convert all ICD9 to ICD10 codes present in diagnoses_icd.csv file.
- We use file in utils/mappings/ICD9_to_ICD10_mapping.txt to convert ICD9 to ICD10.
- We then identify the disease label with the first three letters of icd10 codes. For CKD the root is N18.
- You can use preprocessing/day_intervals_preproc/disease_cohort.py to see what codes come under every root node.
- For N18, the ICD 10 codes are N181, N182, N183, N184, N185, N186, N189.
Thanks.
from mimic-iv-data-pipeline.
Related Issues (16)
- Add time information to procedures
- Add time to Medications
- Add time for labs
- Outlier Detection
- Create Function to extract data HOT 1
- create a function to preprocess data
- TypeError: preprocess_features_icu() missing 1 required positional argument: 'left_thresh'
- Errors exist in '9. Deep Learning Models' and '10. Running BEHRT' HOT 2
- Using hospital labs for ICU prediction tasks? HOT 4
- System hardware configuration suggested for the pipeline? HOT 2
- No license is declared HOT 1
- Issue of prediction window HOT 1
- Option to load raw notes?
- Code for Labs/Vitals Fetures Selection, that was mentioned in the paper.
- non-ICU data
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