Application of STREAM-URO and APPRAISE-AI reporting standards for artificial intelligence studies in pediatric urology: A case example with pediatric hydronephrosis.

Journal: Journal of pediatric urology
Published Date: Jan 29, 2024

Abstract

INTRODUCTION: Artificial intelligence (AI) and machine learning (ML) in pediatric urology is gaining increased popularity and credibility. However, the literature lacks standardization in reporting and there are areas for methodological improvement, which incurs difficulty in comparison between studies and may ultimately hurt clinical implementation of these models. The "STandardized REporting of Applications of Machine learning in UROlogy" (STREAM-URO) framework provides methodological instructions to improve transparent reporting in urology and APPRAISE-AI in a critical appraisal tool which provides quantitative measures for the quality of AI studies. The adoption of these will allow urologists and developers to ensure consistency in reporting, improve comparison, develop better models, and hopefully inspire clinical translation.

Authors

  • Adree Khondker
    Division of Urology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada.
  • Jethro C C Kwong
    Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
  • Mandy Rickard
    Department of Surgery, The Hospital for Sick Children, Toronto, Ontario, Canada.
  • Lauren Erdman
    Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada.
  • Jin K Kim
    Division of Urology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada.
  • Ihtisham Ahmad
    Division of Urology, Department of Surgery, The Hospital for Sick Children, Toronto, ON, Canada.
  • John Weaver
    Division of Urology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104, USA.
  • Nicolás Fernández
    Division of Urology, Hospital Universitario San Ignacio, Pontificia Universidad Javeriana, School of Medicine, Bogotá D.C., Colombia.
  • Gregory E Tasian
    Department of Surgery, Division of Pediatric Urology, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States; Center for Pediatric Clinical Effectiveness, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States; Department of Biostatistics, Epidemiology, and Informatics, The University of Pennsylvania, Philadelphia, PA, 19104, United States.
  • Girish S Kulkarni
    Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada; Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Temerty Centre for AI Research and Education in Medicine, University of Toronto, Toronto, ON, Canada.
  • Armando J Lorenzo
    Department of Surgery, The Hospital for Sick Children, Toronto, Ontario, Canada.

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