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  "access_rights": "",
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  "author": "Adrian Galdran",
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  "author_email": "",
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  "author_email": "",
            
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  "defined_in": "https://doi.org/10.1007/978-3-030-87240-3_31",
            
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  "doi": "10.57702/7h93qw5w",
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  "doi": "10.57702/7h93qw5w",
            
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  "doi_date_published": null,
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  "doi_date_published": "2024-12-16",
            
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  "doi_publisher": "TIB",
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Gustavo Carneiro",
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      "extra_author": "Gustavo Carneiro",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Miguel A. Gonz\u00e1lez Ballester",
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      "extra_author": "Miguel A. Gonz\u00e1lez Ballester",
            
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      "orcid": ""
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      "orcid": ""
            
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    }
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    }
            
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  ],
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      "description": "",
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      "description": "",
            
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      "display_name": "Imbalanced Data",
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      "display_name": "Imbalanced Data",
            
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      "image_display_url": "",
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      "name": "imbalanced-data",
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      "name": "imbalanced-data",
            
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      "title": "Imbalanced Data"
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      "title": "Imbalanced Data"
            
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    },
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    },
            
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Medical Image Classification",
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      "display_name": "Medical Image Classification",
            
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      "image_display_url": "",
            
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      "name": "medical-image-classification",
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      "name": "medical-image-classification",
            
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      "title": "Medical Image Classification"
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      "title": "Medical Image Classification"
            
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    }
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  "name": 
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  "name": 
            
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"balanced-mixup-for-highly-imbalanced-medical-image-classification",
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"balanced-mixup-for-highly-imbalanced-medical-image-classification",
            
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  "notes": "Highly imbalanced datasets are ubiquitous in medical image 
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  "notes": "Highly imbalanced datasets are ubiquitous in medical image 
            
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classification problems. In such problems, it is often the case that 
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classification problems. In such problems, it is often the case that 
            
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rare classes associated to less prevalent diseases are severely 
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rare classes associated to less prevalent diseases are severely 
            
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under-represented in labeled databases, typically resulting in poor 
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under-represented in labeled databases, typically resulting in poor 
            
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performance of machine learning algorithms due to overfitting in the 
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performance of machine learning algorithms due to overfitting in the 
            
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learning process.",
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learning process.",
            
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      "created": "2024-12-16T18:25:36",
            
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      "description": "The json representation of the dataset with its 
            
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distributions based on DCAT.",
            
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      "format": "JSON",
            
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  "tags": [
            
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      "name": "Balanced-MixUp",
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      "id": "e5690de3-5cca-4b37-b5d8-c1619295296e",
            
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      "name": "Imbalanced Data",
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      "name": "Imbalanced Data",
            
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      "display_name": "Medical Image Classification",
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      "display_name": "Medical Image Classification",
            
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      "id": "3105e0ff-070a-4fb7-8350-723e2264eb45",
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      "id": "3105e0ff-070a-4fb7-8350-723e2264eb45",
            
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      "name": "Medical Image Classification",
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      "name": "Medical Image Classification",
            
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    }
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    }
            
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  ],
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  ],
            
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  "title": "Balanced-MixUp for Highly Imbalanced Medical Image 
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  "title": "Balanced-MixUp for Highly Imbalanced Medical Image 
            
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Classification",
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Classification",
            
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  "type": "dataset",
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  "version": ""
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  "version": ""
            
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}
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}