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  "accrualPeriodicity": "",
            
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  "author": "Philipp D. Rohde",
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  "author": "Philipp D. Rohde",
            
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  "author_email": "",
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  "author_email": "",
            
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  "creator_user_id": "b6005781-6560-475f-aeea-d834a83f0d8f",
            
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  "defined_in": "https://doi.org/10.1016/j.inffus.2024.102557",
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  "defined_in": "https://doi.org/10.1016/j.inffus.2024.102557",
            
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  "doi": "10.57702/4qixxfy9",
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  "doi": "10.57702/4qixxfy9",
            
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  "doi_date_published": null,
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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": "Antonio Jesus Diaz-Honrubia",
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      "extra_author": "Antonio Jesus Diaz-Honrubia",
            
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      "orcid": "0000-0001-5464-0714"
            
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    },
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    {
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    {
            
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      "extra_author": "Emetis Niazmand",
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      "extra_author": "Emetis Niazmand",
            
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      "orcid": "0000-0001-8194-8079"
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      "orcid": "0000-0001-8194-8079"
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Maria-Esther Vidal",
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      "extra_author": "Maria-Esther Vidal",
            
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      "orcid": "0000-0003-1160-8727"
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      "orcid": "0000-0003-1160-8727"
            
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    }
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  "license_title": "Creative Commons Attribution Share-Alike",
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  "license_title": "Creative Commons Attribution Share-Alike",
            
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  "license_url": "http://www.opendefinition.org/licenses/cc-by-sa",
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  "license_url": "http://www.opendefinition.org/licenses/cc-by-sa",
            
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  "maintainer": "",
            
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  "name": "synthetic-breast-cancer-data",
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  "name": "synthetic-breast-cancer-data",
            
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  "notes": "The data is generated using the [Synthetic Data 
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  "notes": "The data is generated using the [Synthetic Data 
            
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Generator](https://github.com/SDM-TIB/Synthetic-Data-Generator) which 
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Generator](https://github.com/SDM-TIB/Synthetic-Data-Generator) which 
            
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generates process-based breast cancer treatment data following the 
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generates process-based breast cancer treatment data following the 
            
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distribution in a real population of breast cancer patients. The 
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distribution in a real population of breast cancer patients. The 
            
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collection comprises a total of 18 data sets, nine for relational 
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collection comprises a total of 18 data sets, nine for relational 
            
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databases and nine for RDF-based knowledge graphs. For each data 
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databases and nine for RDF-based knowledge graphs. For each data 
            
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format, there are three different sizes of data sets:\r\n\r\n+ _Small_ 
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format, there are three different sizes of data sets:\r\n\r\n+ _Small_ 
            
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models 1,000 patients\r\n+ _Medium-sized_ models 10,000 patients\r\n+ 
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models 1,000 patients\r\n+ _Medium-sized_ models 10,000 patients\r\n+ 
            
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_Large_ models 100,000 patients\r\n\r\nThere are three data sets of 
61
_Large_ models 100,000 patients\r\n\r\nThere are three data sets of 
            
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each size. They differ in the parameter used for the mutation 
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each size. They differ in the parameter used for the mutation 
            
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probability of the data generator. The lower this value is, the closer 
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probability of the data generator. The lower this value is, the closer 
            
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the data is to following the treatment guideline for breast cancer 
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the data is to following the treatment guideline for breast cancer 
            
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patients with an amplified HER2 gene.",
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patients with an amplified HER2 gene.",
            
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    "description": "The German National Library of Science and 
            
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Technology, abbreviated TIB, is the national library of the Federal 
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Technology, abbreviated TIB, is the national library of the Federal 
            
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Republic of Germany for all fields of engineering, technology, and the 
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Republic of Germany for all fields of engineering, technology, and the 
            
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natural sciences.",
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natural sciences.",
            
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