Dataset Information

A Method Based on Artificial Intelligence To Fully Automatize The Evaluation of Bovine Blastocyst Images.

ABSTRACT: Morphological analysis is the standard method of assessing embryo quality; however, its inherent subjectivity tends to generate discrepancies among evaluators. Using genetic algorithms and artificial neural networks (ANNs), we developed a new method for embryo analysis that is more robust and reliable than standard methods. Bovine blastocysts produced in vitro were classified as grade 1 (excellent or good), 2 (fair), or 3 (poor) by three experienced embryologists according to the International Embryo Technology Society (IETS) standard. The images (n = 482) were subjected to automatic feature extraction, and the results were used as input for a supervised learning process. One part of the dataset (15%) was used for a blind test posterior to the fitting, for which the system had an accuracy of 76.4%. Interestingly, when the same embryologists evaluated a sub-sample (10%) of the dataset, there was only 54.0% agreement with the standard (mode for grades). However, when using the ANN to assess this sub-sample, there was 87.5% agreement with the modal values obtained by the evaluators. The presented methodology is covered by National Institute of Industrial Property (INPI) and World Intellectual Property Organization (WIPO) patents and is currently undergoing a commercial evaluation of its feasibility.

SUBMITTER: Rocha JC

PROVIDER: S-EPMC5550425 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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A Method Based on Artificial Intelligence To Fully Automatize The Evaluation of Bovine Blastocyst Images.

Rocha José Celso JC Passalia Felipe José FJ Matos Felipe Delestro FD Takahashi Maria Beatriz MB Ciniciato Diego de Souza DS Maserati Marc Peter MP Alves Mayra Fernanda MF de Almeida Tamie Guibu TG Cardoso Bruna Lopes BL Basso Andrea Cristina AC Nogueira Marcelo Fábio Gouveia MFG

Scientific reports 20170809 1

Morphological analysis is the standard method of assessing embryo quality; however, its inherent subjectivity tends to generate discrepancies among evaluators. Using genetic algorithms and artificial neural networks (ANNs), we developed a new method for embryo analysis that is more robust and reliable than standard methods. Bovine blastocysts produced in vitro were classified as grade 1 (excellent or good), 2 (fair), or 3 (poor) by three experienced embryologists according to the International E ...[more]

PMID: 28794478

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Dataset Information

A Method Based on Artificial Intelligence To Fully Automatize The Evaluation of Bovine Blastocyst Images.

Publications

A Method Based on Artificial Intelligence To Fully Automatize The Evaluation of Bovine Blastocyst Images.

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