Artificial intelligence-simplified information to advance reproductive genetic literacy and health equity.

Abstract

Authors

• Marjan Naghdi
  Department of Clinical Genetics, Maastricht University Medical Centre (MUMC+), Maastricht, The Netherlands.
• Ping Cao
  Department of Clinical Genetics, Maastricht University Medical Center+ (MUMC+), Maastricht, The Netherlands.
• Rick Essers
  Department of Clinical Genetics, Maastricht University Medical Centre (MUMC+), Maastricht, The Netherlands.
• Malou Heijligers
  Department of Clinical Genetics, Maastricht University Medical Centre (MUMC+), Maastricht, The Netherlands.
• Aimee D C Paulussen
  Department of Clinical Genetics, Maastricht University Medical Centre (MUMC+), Maastricht, The Netherlands.
• Arie van der Lugt
  Section Teaching and Innovation of Learning (STIL), Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.
• Robert A C Ruiter
  Department of Work and Social Psychology, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.
• Wendy A G van Zelst-Stams
  Department of Clinical Genetics, Maastricht University Medical Centre (MUMC+), Maastricht, The Netherlands.
• Andres Salumets
  Division of Obstetrics and Gynecology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden; Competence Centre on Health Technologies, Tartu, Estonia; Department of Obstetrics and Gynaecology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia.
• Masoud Zamani Esteki
  Department of Clinical Genetics, Maastricht University Medical Center+ (MUMC+), Maastricht, The Netherlands.

Keywords

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