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  "groups": [],
            
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  "id": "4474dd3c-fdb0-4749-a163-8ffbced7905c",
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  "id": "4474dd3c-fdb0-4749-a163-8ffbced7905c",
            
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  "isopen": true,
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  "isopen": true,
            
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  "license_id": "cc-by",
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  "license_id": "cc-by",
            
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  "license_title": "Creative Commons Attribution",
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  "license_title": "Creative Commons Attribution",
            
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  "license_url": "http://www.opendefinition.org/licenses/cc-by",
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  "license_url": "http://www.opendefinition.org/licenses/cc-by",
            
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  "maintainer": "Data tester",
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  "maintainer": "Data tester",
            
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  "maintainer_email": "medpacslin@gmail.com",
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  "maintainer_email": "medpacslin@gmail.com",
            
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  "metadata_created": "2023-03-28T02:39:48.272191",
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  "metadata_created": "2023-03-28T02:39:48.272191",
            
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  "metadata_modified": "2023-12-12T07:02:46.918246",
            
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  "name": "ihd-ct",
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  "name": "ihd-ct",
            
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  "notes": "## Overview\r\n\r\nThis dataset, featured in the RSNA 
17
  "notes": "## Overview\r\n\r\nThis dataset, featured in the RSNA 
            
18
Intracranial Hemorrhage Detection challenge on Kaggle, offers a rich 
18
Intracranial Hemorrhage Detection challenge on Kaggle, offers a rich 
            
19
collection of brain CT images. It is meticulously categorized into 
19
collection of brain CT images. It is meticulously categorized into 
            
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seven distinct classes: 'any', 'epidural', 'intraparenchymal', 
20
seven distinct classes: 'any', 'epidural', 'intraparenchymal', 
            
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'intraventricular', 'none', 'subarachnoid', and 'subdural'. Each 
21
'intraventricular', 'none', 'subarachnoid', and 'subdural'. Each 
            
22
category is represented by 1000 DICOM files, providing a balanced and 
22
category is represented by 1000 DICOM files, providing a balanced and 
            
23
extensive dataset for analysis and machine learning 
23
extensive dataset for analysis and machine learning 
            
24
applications.\r\n\r\n## Dataset Details\r\n\r\n__Categories__: Any, 
24
applications.\r\n\r\n## Dataset Details\r\n\r\n__Categories__: Any, 
            
25
Epidural, Intraparenchymal, Intraventricular, None, Subarachnoid, 
25
Epidural, Intraparenchymal, Intraventricular, None, Subarachnoid, 
            
t
26
Subdural\r\n__Files__: 1000 DICOM files per category\r\n__Total 
t
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Subdural/n\r\n__Files__: 1000 DICOM files per category\r\n__Total 
            
27
Images__: 7000 DICOM files\r\n__Source__: RSNA Intracranial Hemorrhage 
27
Images__: 7000 DICOM files\r\n__Source__: RSNA Intracranial Hemorrhage 
            
28
Detection Challenge on Kaggle\r\nThe source of the dataset (from 
28
Detection Challenge on Kaggle\r\nThe source of the dataset (from 
            
29
Kaggle): 
29
Kaggle): 
            
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gle.com/competitions/rsna-intracranial-hemorrhage-detection/data\r\n",
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gle.com/competitions/rsna-intracranial-hemorrhage-detection/data\r\n",
            
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    "title": "National Yang Ming Chiao Tung University",
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