Enhancing Patient Safety in Prehospital Environment: Analyzing Patient Perspectives on Non-Transport Decisions With Natural Language Processing and Machine Learning.

Abstract

Authors

• Hassan Farhat
  Ambulance Service, Hamad Medical Corporation, Doha, Qatar.
• Guillaume Alinier
  Hamad Medical Corporation Ambulance Service, Doha P.O. Box 3050, Qatar.
• Reem Tluli
  From the Ambulance Service, Hamad Medical Corporation, Doha, Qatar.
• Montaha Chakif
  From the Ambulance Service, Hamad Medical Corporation, Doha, Qatar.
• Fatma Babay Ep Rekik
  From the Ambulance Service, Hamad Medical Corporation, Doha, Qatar.
• Ma Cleo Alcantara
  From the Ambulance Service, Hamad Medical Corporation, Doha, Qatar.
• Padarath Gangaram
  Faculty of Health Sciences, Durban University of Technology, Durban, South Africa.
• Kawther El Aifa
  Ambulance Service, Hamad Medical Corporation, Doha, Qatar.
• Ahmed Makhlouf
  Ambulance Service, Hamad Medical Corporation, Doha, Qatar.
• Ian Howland
  Ambulance Service, Hamad Medical Corporation, Doha, Qatar.
• Mohamed Chaker Khenissi
  Ambulance Service, Hamad Medical Corporation, Doha, Qatar.
• Sailesh Chauhan
  From the Ambulance Service, Hamad Medical Corporation, Doha, Qatar.
• Cyrine Abid
  Laboratory of Screening Cellular and Molecular Process, Centre of Biotechnology of Sfax, University of Sfax, Sfax, Tunisia.
• Nicholas Castle
  Ambulance Service, Hamad Medical Corporation, Doha, Qatar.
• Loua Al Shaikh
  From the Ambulance Service, Hamad Medical Corporation, Doha, Qatar.
• Moncef Khadhraoui
  Higher Institute of Biotechnology, University of Sfax, Sfax, Tunisia.
• Imed Gargouri
  Faculty of Medicine, University of Sfax, Sfax, Tunisia.
• James Laughton
  Ambulance Service, Hamad Medical Corporation, Doha, Qatar.

Keywords

External Resources