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| """ |
| Created on Wed Apr 17 19:47:32 2024 |
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| @author: yanwe |
| """ |
|
|
| import pandas as pd |
| import shutil |
| import os |
|
|
| test = pd.read_csv('/mnt/de1dcd1c-9be8-42ed-aa06-bb73570121ac/MIMIC_CXR/60k/meta/test.csv', nrows=500) |
| test['path_preproc'] = None |
| for n in range(500): |
| test.loc[n,'path_preproc'] = f'{n}.jpg' |
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| source_file = '/mnt/de1dcd1c-9be8-42ed-aa06-bb73570121ac/MIMIC_CXR/60k/data' |
| target_directory = '/mnt/de1dcd1c-9be8-42ed-aa06-bb73570121ac/cf_app/data/mimic_subset' |
|
|
| for n in range(500): |
| file_name = os.path.join(source_file, test.loc[n,'dicom_id'] + '.jpg') |
| new_name = os.path.join(target_directory, test.loc[n,'path_preproc']) |
| shutil.copy(file_name, new_name) |
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|
| def label_to_name(data): |
| if data['disease_label'] == 0: |
| return "No Finding" |
| elif data['disease_label'] == 1: |
| return "Pleural Effusion" |
| elif data['disease_label'] == 2: |
| return "Pneumonia" |
| else: |
| return "No Finding" |
| |
| def label_to_sex(data): |
| if data['sex_label'] == 0: |
| return "Female" |
| elif data['sex_label'] == 1: |
| return "Male" |
| else: |
| return "Female" |
| |
| def label_to_race(data): |
| if data['race_label'] == 0: |
| return "White" |
| elif data['race_label'] == 1: |
| return "Black" |
| elif data['race_label'] == 2: |
| return "Asian" |
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| test['disease'] = test.apply(label_to_name, axis=1) |
| test['sex'] = test.apply(label_to_sex, axis=1) |
| test['race'] = test.apply(label_to_race, axis=1) |
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| test.to_csv('/mnt/de1dcd1c-9be8-42ed-aa06-bb73570121ac/cf_app/data/mimic_subset/mimic.sample.test.csv') |
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