Cytoplasmic movements of the early human embryo: imaging and artificial intelligence to predict blastocyst development.

Journal: Reproductive biomedicine online
PMID: 33558172

Abstract

RESEARCH QUESTION: Can artificial intelligence and advanced image analysis extract and harness novel information derived from cytoplasmic movements of the early human embryo to predict development to blastocyst?

Authors

  • Giovanni Coticchio
    9.baby Family and Fertility Center, Via Dante, 15, Bologna 40125, Italy. Electronic address: giovanni.coticchio@nove.baby.
  • Giulia Fiorentino
    Department of Biology and Biotechnology 'Lazzaro Spallanzani', University of Pavia, Via Ferrata, 9 27100, Italy; Centre for Health Technology, University of Pavia, Pavia, Italy.
  • Giovanna Nicora
    Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
  • Raffaella Sciajno
    9.baby Family and Fertility Center, Via Dante, 15, Bologna 40125, Italy.
  • Federica Cavalera
    Department of Biology and Biotechnology 'Lazzaro Spallanzani', University of Pavia, Via Ferrata, 9 27100, Italy.
  • Riccardo Bellazzi
    Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
  • Silvia Garagna
    Department of Biology and Biotechnology, University of Pavia, 27100, Pavia, Italy.
  • Andrea Borini
    9.baby Family and Fertility Center, Via Dante, 15, Bologna 40125, Italy.
  • Maurizio Zuccotti
    Department of Biology and Biotechnology, University of Pavia, 27100, Pavia, Italy.

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