Artificial Intelligence and Anorectal Manometry: Automatic Detection and Differentiation of Anorectal Motility Patterns-A Proof-of-Concept Study.

Journal: Clinical and translational gastroenterology
PMID: 36520781

Abstract

INTRODUCTION: Anorectal manometry (ARM) is the gold standard for the evaluation of anorectal functional disorders, prevalent in the population. Nevertheless, the accessibility to this examination is limited, and the complexity of data analysis and report is a significant drawback. This pilot study aimed to develop and validate an artificial intelligence model to automatically differentiate motility patterns of fecal incontinence (FI) from obstructed defecation (OD) using ARM data.

Authors

  • Miguel Mascarenhas Saraiva
    Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, 4200-427, Porto, Portugal; WGO Gastroenterology and Hepatology Training Center, Porto, Portugal; Faculty of Medicine of the University of Porto, Alameda Professor Hernâni Monteiro, Porto 4200-427, Portugal.
  • Maria Vila Pouca
    Department of Mechanical Engineering, Faculty of Engineering of the University of Porto, Porto, Portugal.
  • Tiago Ribeiro
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • João Afonso
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • Hélder Cardoso
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • Pedro Sousa
    Administração Regional De Saúde Do Norte (ARSN), Porto, Portugal.
  • João Ferreira
    Department of Mechanical Engineering, Faculty of Engineering of the University of Porto, Porto, Portugal.
  • Guilherme Macedo
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • Ilario Froehner Junior
    Department of Gastrointestinal Motility, Nossa Senhora das Graças Hospital, Curitiba, Paraná, Brazil.

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