Use of artificial intelligence in obstetric and gynaecological diagnostics: a protocol for a systematic review and meta-analysis.

Journal: BMJ open
Published Date: May 8, 2024

Abstract

INTRODUCTION: Emerging developments in applications of artificial intelligence (AI) in healthcare offer the opportunity to improve diagnostic capabilities in obstetrics and gynaecology (O&G), ensuring early detection of pathology, optimal management and improving survival. Consensus on a robust AI healthcare framework is crucial for standardising protocols that promote data privacy and transparency, minimise bias, and ensure patient safety. Here, we describe the study protocol for a systematic review and meta-analysis to evaluate current applications of AI in O&G diagnostics with consideration of reporting standards used and their ethical implications. This protocol is written following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) 2015 checklist.

Authors

  • Anjalee Chaurasia
    School of Medicine, Imperial College London, London, UK anjalee.chaurasia18@gmail.com.
  • Georgia Curry
    School of Medicine, Imperial College London, London, UK.
  • Yi Zhao
    Department of Biostatistics and Health Data Science, Indiana University School of Medicine.
  • Fatema Dawoodbhoy
    Barking Havering and Redbridge Hospitals NHS Trust, Romford, UK.
  • Jennifer Green
    Department of Obstetrics & Gynaecology, North West Anglia NHS Foundation Trust, Peterborough, UK.
  • Matilde Vaninetti
    Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
  • Nishel Shah
    Department of Metabolism, Digestion and Reproduction, Chelsea and Westminster Hospital, London, UK.
  • Orene Greer
    Department of Metabolism, Digestion and Reproduction, Chelsea and Westminster Hospital, London, UK.

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