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README.md
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path: data/train-*
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---
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# Dataset Card for Dataset Name
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<!-- Provide a longer summary of what this dataset is. -->
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- **Shared by [optional]:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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### Dataset Sources [optional]
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<!-- Provide the basic links for the dataset. -->
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- **Repository:**
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## Uses
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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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[More Information Needed]
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## Dataset Structure
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<!-- Motivation for the creation of this dataset. -->
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### Source Data
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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#### Data Collection and Processing
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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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Composition of the dataset:
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- [RFMID](https://www.kaggle.com/datasets/andrewmvd/retinal-disease-classification)
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- [ODIR](https://www.kaggle.com/datasets/andrewmvd/ocular-disease-recognition-odir5k)
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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 [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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<!-- 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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[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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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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## Citation
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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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**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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## Dataset Card Authors [optional]
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## Dataset Card
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data_files:
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path: data/train-*
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license: mit
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pretty_name: big-dataset-fundus-images
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---
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# Dataset Card for Dataset Name
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<!-- Provide a longer summary of what this dataset is. -->
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**FISSL** is a dataset resulting from the combination of 4 different retinal image datasets (RFMID, ODIR, eyePACS, APTOS).
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All images have been resized to 224x224 and converted to .png format
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- **Curated by:** Diego Hernández
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- **License:** MIT
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### Dataset Sources
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<!-- Provide the basic links for the dataset. -->
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- **Repository:**
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- [huggingface dataset RFMID](https://huggingface.co/datasets/bumbledeep/rfmid)
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- [huggingface dataset ODIR](https://huggingface.co/datasets/bumbledeep/odir)
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- [huggingface dataset eyePACS](https://huggingface.co/datasets/bumbledeep/eyepacs)
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- [huggingface dataset APTOS](https://huggingface.co/datasets/bumbledeep/aptos)
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## Uses
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<!-- This section describes suitable use cases for the dataset. -->
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This version of the dataset is unlabeled and intended for feature extraction. More specifically, it was designed with **self-supervised learning** in mind.
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## Dataset Structure
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<!-- Motivation for the creation of this dataset. -->
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The images have not been edited except for resizing. No additional processing has been performed.
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### Source Data
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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The used sources are properly described in each dataset card of the list given in the Dataset Sources section.
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#### Data Collection and Processing
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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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Composition of the dataset (original sources):
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- [RFMID](https://www.kaggle.com/datasets/andrewmvd/retinal-disease-classification)
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- [ODIR](https://www.kaggle.com/datasets/andrewmvd/ocular-disease-recognition-odir5k)
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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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See the dataset cards of each source.
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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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The heterogeneity in the images can be quite high due to the lack of a rigorous standardization process. This may affect the quality of the analyses performed.
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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It is recommended to preprocess the images before using them to train deep learning models.
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## Citation
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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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If you use this dataset, please consider mentioning this repository or my Hugging Face username :)
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## Dataset Card Authors
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bumbledeep
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