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Data sharing: using blockchain and decentralized data technologies to unlock the potential of artificial intelligence: What can assisted reproduction learn from other areas of medicine?
Hickman, Cristina Fontes Lindemann; Alshubbar, Hoor; Chambost, Jerome; Jacques, Celine; Pena, Chris-Alexandre; Drakeley, Andrew; Freour, Thomas.
Afiliación
  • Hickman CFL; Apricity, Paris, France; Institute of Reproduction and Developmental Biology, Imperial College London, London, United Kingdom; TMRW Life Sciences, New York, New York.
  • Alshubbar H; Apricity, Paris, France; Institute of Reproduction and Developmental Biology, Imperial College London, London, United Kingdom.
  • Chambost J; Apricity, Paris, France.
  • Jacques C; Apricity, Paris, France.
  • Pena CA; Apricity, Paris, France.
  • Drakeley A; Hewitt Fertility Centre, Liverpool Women's Hospital, Liverpool, United Kingdom.
  • Freour T; Service de Médecine et Biologie de la Reproduction, CHU de Nantes, Nantes, France; Centre de Recherche en Transplantation et Immunologie, INSERM, Université de Nantes, Nantes, France.
Fertil Steril ; 114(5): 927-933, 2020 11.
Article en En | MEDLINE | ID: mdl-33160515
The extension of blockchain use for nonfinancial domains has revealed opportunities to the health care sector that answer the need for efficient and effective data and information exchanges in a secure and transparent manner. Blockchain is relatively novel in health care and particularly for data analytics, although there are examples of improvements achieved. We provide a systematic review of blockchain uses within the health care industry, with a particular focus on the in vitro fertilization (IVF) field. Blockchain technology in the fertility sector, including data sharing collaborations compliant with ethical data handling within confines of international law, allows for large-scale prospective cohort studies to proceed at an international scale. Other opportunities include gamete donation and matching, consent sharing, and shared resources between different clinics.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Técnicas Reproductivas Asistidas / Difusión de la Información / Cadena de Bloques Tipo de estudio: Observational_studies / Systematic_reviews Límite: Humans Idioma: En Revista: Fertil Steril Año: 2020 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Técnicas Reproductivas Asistidas / Difusión de la Información / Cadena de Bloques Tipo de estudio: Observational_studies / Systematic_reviews Límite: Humans Idioma: En Revista: Fertil Steril Año: 2020 Tipo del documento: Article