TY - JOUR
T1 - Artificial intelligence for the early detection of colorectal cancer
T2 - A comprehensive review of its advantages and misconceptions
AU - Viscaino, Michelle
AU - Bustos, Javier Torres
AU - Muñoz, Pablo
AU - Cheein, Cecilia Auat
AU - Cheein, Fernando Auat
N1 - Funding Information:
Supported by Chilean National Agency for Research and Development (ANID), No. FB0008; and CONICYT-PCHA/Doctorado Nacional, No. 2018-21181420.
Publisher Copyright:
© 2021 Baishideng Publishing Group Co., Limited. All rights reserved.
PY - 2021/10/14
Y1 - 2021/10/14
N2 - Colorectal cancer (CRC) was the second-ranked worldwide type of cancer during 2020 due to the crude mortality rate of 12.0 per 100000 inhabitants. It can be prevented if glandular tissue (adenomatous polyps) is detected early. Colonoscopy has been strongly recommended as a screening test for both early cancer and adenomatous polyps. However, it has some limitations that include the high polyp miss rate for smaller (< 10 mm) or flat polyps, which are easily missed during visual inspection. Due to the rapid advancement of technology, artificial intelligence (AI) has been a thriving area in different fields, including medicine. Particularly, in gastroenterology AI software has been included in computer-aided systems for diagnosis and to improve the assertiveness of automatic polyp detection and its classification as a preventive method for CRC. This article provides an overview of recent research focusing on AI tools and their applications in the early detection of CRC and adenomatous polyps, as well as an insightful analysis of the main advantages and misconceptions in the field.
AB - Colorectal cancer (CRC) was the second-ranked worldwide type of cancer during 2020 due to the crude mortality rate of 12.0 per 100000 inhabitants. It can be prevented if glandular tissue (adenomatous polyps) is detected early. Colonoscopy has been strongly recommended as a screening test for both early cancer and adenomatous polyps. However, it has some limitations that include the high polyp miss rate for smaller (< 10 mm) or flat polyps, which are easily missed during visual inspection. Due to the rapid advancement of technology, artificial intelligence (AI) has been a thriving area in different fields, including medicine. Particularly, in gastroenterology AI software has been included in computer-aided systems for diagnosis and to improve the assertiveness of automatic polyp detection and its classification as a preventive method for CRC. This article provides an overview of recent research focusing on AI tools and their applications in the early detection of CRC and adenomatous polyps, as well as an insightful analysis of the main advantages and misconceptions in the field.
KW - Artificial intelligence
KW - Colorectal cancer
KW - Colorectal polyps
KW - Deep learning
KW - Machine learning
KW - Medical images
UR - http://www.scopus.com/inward/record.url?scp=85116999949&partnerID=8YFLogxK
U2 - 10.3748/wjg.v27.i38.6399
DO - 10.3748/wjg.v27.i38.6399
M3 - Review article
C2 - 34720530
AN - SCOPUS:85116999949
SN - 1007-9327
VL - 27
SP - 6399
EP - 6414
JO - World Journal of Gastroenterology
JF - World Journal of Gastroenterology
IS - 38
ER -
