The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy

Ilona Vilkoite (Coresponding Author), Ivars Tolmanis, Hosams Abu Meri, Inese Polaka, Linda Mezmale, Linda Anarkulova, Marcis Leja, Aivars Lejnieks

Research output: Contribution to journalArticlepeer-review


BACKGROUND: Colorectal cancer (CRC) is the third most common cancer worldwide. Colonoscopy is the gold standard examination that reduces the morbidity and mortality of CRC. Artificial intelligence (AI) could be useful in reducing the errors of the specialist and in drawing attention to the suspicious area.

METHODS: A prospective single-center randomized controlled study was conducted in an outpatient endoscopy unit with the aim of evaluating the usefulness of AI-assisted colonoscopy in PDR and ADR during the day time. It is important to understand how already available CADe systems improve the detection of polyps and adenomas in order to make a decision about their routine use in practice. In the period from October 2021 to February 2022, 400 examinations (patients) were included in the study. One hundred and ninety-four patients were examined using the ENDO-AID CADe artificial intelligence device (study group), and 206 patients were examined without the artificial intelligence (control group).

RESULTS: None of the analyzed indicators (PDR and ADR during morning and afternoon colonoscopies) showed differences between the study and control groups. There was an increase in PDR during afternoon colonoscopies, as well as ADR during morning and afternoon colonoscopies.

CONCLUSIONS: Based on our results, the use of AI systems in colonoscopies is recommended, especially in circumstances of an increase of examinations. Additional studies with larger groups of patients at night are needed to confirm the already available data.

Original languageEnglish
Article number701
Issue number4
Publication statusPublished - 13 Feb 2023


  • colorectal cancer
  • Adenoma
  • colonoscopy
  • polyps
  • artificial intelligence

Field of Science*

  • 3.2 Clinical medicine

Publication Type*

  • 1.1. Scientific article indexed in Web of Science and/or Scopus database


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