Please use this identifier to cite or link to this item:
10.3390/diagnostics13040701
Title: | The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy |
Authors: | Vilkoite, Ilona Tolmanis, Ivars Meri, Hosams Abu Polaka, Inese Mezmale, Linda Anarkulova, Linda Leja, Marcis Lejnieks, Aivars Department of Doctoral Studies Department of Internal Diseases |
Keywords: | colorectal cancer;Adenoma;colonoscopy;polyps;artificial intelligence;3.2 Clinical medicine;1.1. Scientific article indexed in Web of Science and/or Scopus database;SDG 3 - Good Health and Well-being |
Issue Date: | 13-Feb-2023 |
Citation: | Vilkoite , I , Tolmanis , I , Meri , H A , Polaka , I , Mezmale , L , Anarkulova , L , Leja , M & Lejnieks , A 2023 , ' The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy ' , Diagnostics , vol. 13 , no. 4 , 701 . https://doi.org/10.3390/diagnostics13040701 |
Abstract: | 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. |
Description: | Funding Information: The project is funded by the European Regional Development Fund (ERDF) 1.1.1.1. project “Practical Studies”, 4th phase, project ID Nr. 1.1.1.1/20/A/035. Publisher Copyright: © 2023 by the authors. |
DOI: | 10.3390/diagnostics13040701 |
ISSN: | 2075-4418 |
Appears in Collections: | Research outputs from Pure / Zinātniskās darbības rezultāti no ZDIS Pure |
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diagnostics_13_00701.pdf | 7.84 MB | Adobe PDF | View/Open |
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