Artificial Intelligence-assisted colonoscopy and colorectal cancer screening : Where are we going?
Copyright © 2024 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved..
Colorectal cancer is a significant global health concern, necessitating effective screening strategies to reduce its incidence and mortality rates. Colonoscopy plays a crucial role in the detection and removal of colorectal neoplastic precursors. However, there are limitations and variations in the performance of endoscopists, leading to missed lesions and suboptimal outcomes. The emergence of artificial intelligence (AI) in endoscopy offers promising opportunities to improve the quality and efficacy of screening colonoscopies. In particular, AI applications, including computer-aided detection (CADe) and computer-aided characterization (CADx), have demonstrated the potential to enhance adenoma detection and optical diagnosis accuracy. Additionally, AI-assisted quality control systems aim to standardize the endoscopic examination process. This narrative review provides an overview of AI principles and discusses the current knowledge on AI-assisted endoscopy in the context of screening colonoscopies. It highlights the significant role of AI in improving lesion detection, characterization, and quality assurance during colonoscopy. However, further well-designed studies are needed to validate the clinical impact and cost-effectiveness of AI-assisted colonoscopy before its widespread implementation.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2024 |
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| Enthalten in: |
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver - (2024) vom: 07. März |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Spadaccini, Marco [VerfasserIn] |
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| Links: |
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| Themen: |
Artificial intelligence |
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| Anmerkungen: |
Date Revised 08.03.2024 published: Print-Electronic Citation Status Publisher |
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| doi: |
10.1016/j.dld.2024.01.203 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM369486218 |
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| 520 | |a Copyright © 2024 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved. | ||
| 520 | |a Colorectal cancer is a significant global health concern, necessitating effective screening strategies to reduce its incidence and mortality rates. Colonoscopy plays a crucial role in the detection and removal of colorectal neoplastic precursors. However, there are limitations and variations in the performance of endoscopists, leading to missed lesions and suboptimal outcomes. The emergence of artificial intelligence (AI) in endoscopy offers promising opportunities to improve the quality and efficacy of screening colonoscopies. In particular, AI applications, including computer-aided detection (CADe) and computer-aided characterization (CADx), have demonstrated the potential to enhance adenoma detection and optical diagnosis accuracy. Additionally, AI-assisted quality control systems aim to standardize the endoscopic examination process. This narrative review provides an overview of AI principles and discusses the current knowledge on AI-assisted endoscopy in the context of screening colonoscopies. It highlights the significant role of AI in improving lesion detection, characterization, and quality assurance during colonoscopy. However, further well-designed studies are needed to validate the clinical impact and cost-effectiveness of AI-assisted colonoscopy before its widespread implementation | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Cancer | |
| 650 | 4 | |a Colonoscopy | |
| 650 | 4 | |a Screening | |
| 700 | 1 | |a Troya, Joel |e verfasserin |4 aut | |
| 700 | 1 | |a Khalaf, Kareem |e verfasserin |4 aut | |
| 700 | 1 | |a Facciorusso, Antonio |e verfasserin |4 aut | |
| 700 | 1 | |a Maselli, Roberta |e verfasserin |4 aut | |
| 700 | 1 | |a Hann, Alexander |e verfasserin |4 aut | |
| 700 | 1 | |a Repici, Alessandro |e verfasserin |4 aut | |
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