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The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy
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 suspiciou...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955100/ https://www.ncbi.nlm.nih.gov/pubmed/36832189 http://dx.doi.org/10.3390/diagnostics13040701 |
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author | Vilkoite, Ilona Tolmanis, Ivars Meri, Hosams Abu Polaka, Inese Mezmale, Linda Anarkulova, Linda Leja, Marcis Lejnieks, Aivars |
author_facet | Vilkoite, Ilona Tolmanis, Ivars Meri, Hosams Abu Polaka, Inese Mezmale, Linda Anarkulova, Linda Leja, Marcis Lejnieks, Aivars |
author_sort | Vilkoite, Ilona |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9955100 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99551002023-02-25 The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy Vilkoite, Ilona Tolmanis, Ivars Meri, Hosams Abu Polaka, Inese Mezmale, Linda Anarkulova, Linda Leja, Marcis Lejnieks, Aivars Diagnostics (Basel) Article 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. MDPI 2023-02-13 /pmc/articles/PMC9955100/ /pubmed/36832189 http://dx.doi.org/10.3390/diagnostics13040701 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Vilkoite, Ilona Tolmanis, Ivars Meri, Hosams Abu Polaka, Inese Mezmale, Linda Anarkulova, Linda Leja, Marcis Lejnieks, Aivars The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy |
title | The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy |
title_full | The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy |
title_fullStr | The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy |
title_full_unstemmed | The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy |
title_short | The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy |
title_sort | role of an artificial intelligence method of improving the diagnosis of neoplasms by colonoscopy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955100/ https://www.ncbi.nlm.nih.gov/pubmed/36832189 http://dx.doi.org/10.3390/diagnostics13040701 |
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