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Title:           An annotated human blastocyst dataset to benchmark deep learning architectures for in vitro fertilization
Subject:         Scientific Data, doi:10.1038/s41597-023-02182-3
Keywords:        
Author:          Florian Kromp
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     Item: 
      Title: An annotated human blastocyst dataset to benchmark deep learning architectures for in vitro fertilization
      Children: 
       Item: 
        Title: Background & Summary
       Item: 
        Title: Methods
        Children: 
         Item: 
          Title: Participants and ethics. 
         Item: 
          Title: Embryo development. 
         Item: 
          Title: Blastocyst imaging. 
         Item: 
          Title: Clinical annotations. 
         Item: 
          Title: Gardner score consortium annotation. 
          Children: 
           Item: 
            Title: Gardner criteria. 
           Item: 
            Title: Consortium annotation. 
           Item: 
            Title: Refined consortium agreement. 
       Item: 
        Title: Data Records
        Children: 
         Item: 
          Title: Deep learning model training. 
       Item: 
        Title: Technical Validation
        Children: 
         Item: 
          Title: Inter-annotator agreement. 
         Item: 
          Title: Benchmark for deep learning models. 
       Item: 
        Title: Acknowledgements
       Item: 
        Title: Fig. 1 Workflow of creating the silver-standard training set and the gold-standard test set involving the Gardner-expert and an international consortium consisting of experienced clinical embryologists.
       Item: 
        Title: Fig. 2 Class assignment distribution of the Gardner criteria within the silver-standard training set and the gold-standard test set.
       Item: 
        Title: Fig. 3 Inter-Annotator agreement (a–c) and deep learning baseline agreement (d–f) with the consensus calculated using Cohen’s Kappa-score.
       Item: 
        Title: Table 1 Parameters provided in the annotations files.
       Item: 
        Title: Table 2 Mean value and standard deviation of the accuracy and the weighted class-average of precision, recall and F1-score of the expert embryologists remaining after consensus filtering, compared to the consensus vote.
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