Multilevel approach to male fertility by machine learning highlights a hidden link between haematological and spermatogenetic cells.

Abstract

Authors

• Daniele Santi
  Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.
• Giorgia Spaggiari
  Unit of Endocrinology, Department of Medical Specialties, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy.
• Andrea Casonati
  Hopenly S.r.l., Vignola, Modena, Italy.
• Livio Casarini
  Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.
• Roberto Grassi
  Department of Radiology, University of Campania "L. Vanvitelli", Naples, Italy.
• Barbara Vecchi
  Hopenly S.r.l., Vignola, Modena, Italy.
• Laura Roli
  Department of Laboratory Medicine and Anatomy Pathology, Azienda USL of Modena, Modena, Italy.
• Maria Cristina De Santis
  Department of Laboratory Medicine and Anatomy Pathology, Azienda USL of Modena, Modena, Italy.
• Giovanna Orlando
  Medical Affair Fertility, Merck-Serono S.p.a, Rome, Italy.
• Enrica Gravotta
  Medical Affairs Fertility EMEA, Merck KGaA, Darmstadt, Germany.
• Enrica Baraldi
  Department of Laboratory Medicine and Anatomy Pathology, Azienda USL of Modena, Modena, Italy.
• Monica Setti
  Service of Clinical Engineering, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy.
• Tommaso Trenti
  Department of Laboratory Medicine and Anatomy Pathology, Azienda USL of Modena, Modena, Italy.
• Manuela Simoni
  Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.

Keywords

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