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Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening

Colorectal cancer (CRC) is the third most common cancer worldwide, with the highest incidence reported in high-income countries. However, because of the slow progression of neoplastic precursors, along with the opportunity for their endoscopic detection and resection, a well-designed endoscopic scre...

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Autores principales: Spadaccini, Marco, Massimi, Davide, Mori, Yuichi, Alfarone, Ludovico, Fugazza, Alessandro, Maselli, Roberta, Sharma, Prateek, Facciorusso, Antonio, Hassan, Cesare, Repici, Alessandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047293/
https://www.ncbi.nlm.nih.gov/pubmed/36980409
http://dx.doi.org/10.3390/diagnostics13061102
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author Spadaccini, Marco
Massimi, Davide
Mori, Yuichi
Alfarone, Ludovico
Fugazza, Alessandro
Maselli, Roberta
Sharma, Prateek
Facciorusso, Antonio
Hassan, Cesare
Repici, Alessandro
author_facet Spadaccini, Marco
Massimi, Davide
Mori, Yuichi
Alfarone, Ludovico
Fugazza, Alessandro
Maselli, Roberta
Sharma, Prateek
Facciorusso, Antonio
Hassan, Cesare
Repici, Alessandro
author_sort Spadaccini, Marco
collection PubMed
description Colorectal cancer (CRC) is the third most common cancer worldwide, with the highest incidence reported in high-income countries. However, because of the slow progression of neoplastic precursors, along with the opportunity for their endoscopic detection and resection, a well-designed endoscopic screening program is expected to strongly decrease colorectal cancer incidence and mortality. In this regard, quality of colonoscopy has been clearly related with the risk of post-colonoscopy colorectal cancer. Recently, the development of artificial intelligence (AI) applications in the medical field has been growing in interest. Through machine learning processes, and, more recently, deep learning, if a very high numbers of learning samples are available, AI systems may automatically extract specific features from endoscopic images/videos without human intervention, helping the endoscopists in different aspects of their daily practice. The aim of this review is to summarize the current knowledge on AI-aided endoscopy, and to outline its potential role in colorectal cancer prevention.
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spelling pubmed-100472932023-03-29 Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening Spadaccini, Marco Massimi, Davide Mori, Yuichi Alfarone, Ludovico Fugazza, Alessandro Maselli, Roberta Sharma, Prateek Facciorusso, Antonio Hassan, Cesare Repici, Alessandro Diagnostics (Basel) Review Colorectal cancer (CRC) is the third most common cancer worldwide, with the highest incidence reported in high-income countries. However, because of the slow progression of neoplastic precursors, along with the opportunity for their endoscopic detection and resection, a well-designed endoscopic screening program is expected to strongly decrease colorectal cancer incidence and mortality. In this regard, quality of colonoscopy has been clearly related with the risk of post-colonoscopy colorectal cancer. Recently, the development of artificial intelligence (AI) applications in the medical field has been growing in interest. Through machine learning processes, and, more recently, deep learning, if a very high numbers of learning samples are available, AI systems may automatically extract specific features from endoscopic images/videos without human intervention, helping the endoscopists in different aspects of their daily practice. The aim of this review is to summarize the current knowledge on AI-aided endoscopy, and to outline its potential role in colorectal cancer prevention. MDPI 2023-03-14 /pmc/articles/PMC10047293/ /pubmed/36980409 http://dx.doi.org/10.3390/diagnostics13061102 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 Review
Spadaccini, Marco
Massimi, Davide
Mori, Yuichi
Alfarone, Ludovico
Fugazza, Alessandro
Maselli, Roberta
Sharma, Prateek
Facciorusso, Antonio
Hassan, Cesare
Repici, Alessandro
Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening
title Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening
title_full Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening
title_fullStr Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening
title_full_unstemmed Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening
title_short Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening
title_sort artificial intelligence-aided endoscopy and colorectal cancer screening
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047293/
https://www.ncbi.nlm.nih.gov/pubmed/36980409
http://dx.doi.org/10.3390/diagnostics13061102
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