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  - medical
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  ---
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- # Dataset Card for Dataset Name
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  <!-- Provide a quick summary of the dataset. -->
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- The kidney-CT-abnormality dataset contains kidney CT scans with normal/abnormal label. Original homepage: https://zenodo.org/records/8043408
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- Note that this dataset was reconstructed from “Dataset for: Kidney abnormality segmentation in thorax-abdomen CT scans” (https://zenodo.org/records/8014290), to fit the 2023 automated universal classification challenges (AUC2023) as stated by the authors.
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  ## Dataset Details
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  ### Dataset Description
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  <!-- Provide a longer summary of what this dataset is. -->
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- This dataset in total is comprised of 986 .mha (medical high-resolution image) files. Each of these files contains multiple layers of CT scans of the kidney.
 
 
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  A .json file is also included, illustrating the abnormality status of each image.
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- ### Dataset Sources [optional]
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  <!-- Provide the basic links for the dataset. -->
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  - **Original Homepage:** https://zenodo.org/records/8043408
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  ## Uses
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  <!-- Address questions around how the dataset is intended to be used. -->
 
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  ### Direct Use
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  <!-- This section describes suitable use cases for the dataset. -->
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- [More Information Needed]
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  ### Out-of-Scope Use
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  <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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- [More Information Needed]
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  ## Dataset Structure
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  <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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- [More Information Needed]
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  ## Dataset Creation
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  ### Curation Rationale
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  <!-- Motivation for the creation of this dataset. -->
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- Kidney diseases can be challenging to detect, while identification or diagnosis is crucial for treatment. This dataset is intended to develop AI and machine learning algorithms for enhanced kidney disease recognition.
 
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- [More Information Needed]
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  ### Source Data
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@@ -67,41 +71,33 @@ https://zenodo.org/records/8043408
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  <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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  https://zenodo.org/records/8014290
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  The original dataset contains “215 thoraxabdomen CT scans with segmentations of the kidney and abnormalities in the kidney”. Note that the original datasets contains in total 38.4G image data in mha format, and there is no .json file indicating the abnormality status. Alternatively, a segmentation kidney image dataset is included.
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- [More Information Needed]
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  #### Who are the source data producers?
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  <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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- [More Information Needed]
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- ### Annotations [optional]
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- <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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- #### Annotation process
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  <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
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- [More Information Needed]
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- #### Who are the annotators?
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-
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  <!-- This section describes the people or systems who created the annotations. -->
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- [More Information Needed]
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  #### Personal and Sensitive Information
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  <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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  The CT scan image file names contain the study ID, indicating the differences in scans. These ids are anonymous and don’t contain any other personal information.
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- [More Information Needed]
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  ## Bias, Risks, and Limitations
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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  ### Recommendations
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@@ -112,29 +108,8 @@ Users should be made aware of the risks, biases and limitations of the dataset.
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  ## Citation [optional]
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  <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
 
 
 
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- **BibTeX:**
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- **APA:**
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- [More Information Needed]
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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- [More Information Needed]
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- ## More Information [optional]
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- [More Information Needed]
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- ## Dataset Card Authors [optional]
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- [More Information Needed]
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- ## Dataset Card Contact
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- [More Information Needed]
 
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  - medical
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  ---
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+ # Kidney-CT-Abnormality
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  <!-- Provide a quick summary of the dataset. -->
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+ This Kidney-CT_Abnormality dataset consists of kidney CT scans with abnormality label.
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+ The original dataset is available at https://zenodo.org/records/8043408.
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  ## Dataset Details
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  ### Dataset Description
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  <!-- Provide a longer summary of what this dataset is. -->
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+
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+ The kidney CT scans contained in this dataset are .mha (medical high-resolution image) files.
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+ In total, there are 986 CT scans, and each contains multiple layers.
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  A .json file is also included, illustrating the abnormality status of each image.
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+ Note that this dataset was reconstructed from “Dataset for: Kidney abnormality segmentation in thorax-abdomen CT scans” (https://zenodo.org/records/8014290), to fit the 2023 automated universal classification challenges (AUC2023) as stated by the authors.
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+
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+ ### Dataset Sources
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  <!-- Provide the basic links for the dataset. -->
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  - **Original Homepage:** https://zenodo.org/records/8043408
 
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  ## Uses
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  <!-- Address questions around how the dataset is intended to be used. -->
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+ This dataset is intended for kidney abnormality classification.
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  ### Direct Use
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  <!-- This section describes suitable use cases for the dataset. -->
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  ### Out-of-Scope Use
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  <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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+
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  ## Dataset Structure
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  <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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+
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  ## Dataset Creation
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  ### Curation Rationale
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  <!-- Motivation for the creation of this dataset. -->
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+ Kidney diseases can be challenging to detect, while identification or diagnosis is crucial for treatment.
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+ This dataset is intended to develop AI and machine learning algorithms for enhanced kidney disease recognition.
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  ### Source Data
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71
  <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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  https://zenodo.org/records/8014290
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  The original dataset contains “215 thoraxabdomen CT scans with segmentations of the kidney and abnormalities in the kidney”. Note that the original datasets contains in total 38.4G image data in mha format, and there is no .json file indicating the abnormality status. Alternatively, a segmentation kidney image dataset is included.
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+
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  #### Who are the source data producers?
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  <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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+ ### Annotations
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84
+ <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
85
 
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  <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
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  <!-- This section describes the people or systems who created the annotations. -->
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+
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  #### Personal and Sensitive Information
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  <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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  The CT scan image file names contain the study ID, indicating the differences in scans. These ids are anonymous and don’t contain any other personal information.
 
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  ## Bias, Risks, and Limitations
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99
  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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  ### Recommendations
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  ## Citation [optional]
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  <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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+ Datasets:
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+ Alves, N., & Boulogne, L. (2023). Kidney CT Abnormality [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8043408
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+ Gabriel E. Humpire-Mamani, Luc Builtjes, Colin Jacobs, Bram van Ginneken, Mathias Prokop, & Ernst Th. Scholten. (2023). Dataset for: Kidney abnormality segmentation in thorax-abdomen CT scans [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8014290
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