Artificial Intelligence Models Could Enhance the Diagnostic Accuracy (DA) of Fecal Immunochemical Test (FIT) in the Detection of Colorectal Adenoma in a Screening Setting.

Journal: Anticancer research
PMID: 39740835

Abstract

BACKGROUND/AIM: This study evaluated the diagnostic accuracy (DA) for colorectal adenomas (CRA), screened by fecal immunochemical test (FIT), using five artificial intelligence (AI) models: logistic regression (LR), support vector machine (SVM), neural network (NN), random forest (RF), and gradient boosting machine (GBM). These models were tested together with clinical features categorized as low-risk (lowR) and high-risk (highR).

Authors

  • Maaret Eskelinen
    Department of Surgery, Kuopio University Hospital and School of Medicine, University of Eastern Finland, Kuopio, Finland; matti.eskelinen@kuh.fi.
  • Tuomas Selander
    Science Service Center, Kuopio University Hospital, Kuopio, Finland.
  • Denise Peixoto Guimarães
    Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos, Brazil.
  • Kai Kaarniranta
    Department of Ophthalmology, Kuopio University Hospital and School of Medicine, University of Eastern Finland, Kuopio, Finland.
  • Kari Syrjänen
    Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos, Brazil.
  • Matti Eskelinen
    Department of Surgery, Kuopio University Hospital and School of Medicine, University of Eastern Finland, Kuopio, Finland.

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