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Deep Learning in Colorectal Cancer Classification:  A Scoping Review.

Authors :
ALALWANI, Rafaa
LUCAS, Augusto
AlZUBAIDI, Mahmoud
SHAH, Hurmat Ali
ALAM, Tanvir
SHAH, Zubair
HOUSEH, Mowafa
Source :
Studies in Health Technology & Informatics; 2023, Vol. 305, p616-619, 4p, 1 Chart
Publication Year :
2023

Abstract

Colorectal cancer (CRC) is one of the most common cancers worldwide, and its diagnosis and classification remain challenging for pathologists and imaging specialists. The use of artificial intelligence (AI) technology, specifically deep learning, has emerged as a potential solution to improve the accuracy and speed of classification while maintaining the quality of care. In this scoping review, we aimed to explore the utilization of deep learning for the classification of different types of colorectal cancer. We searched five databases and selected 45 studies that met our inclusion criteria. Our results show that deep learning models have been used to classify colorectal cancer using various types of data, with histopathology and endoscopy images being the most common. The majority of studies used CNN as their classification model. Our findings provide an overview of the current state of research on deep learning in the classification of colorectal cancer. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09269630
Volume :
305
Database :
Complementary Index
Journal :
Studies in Health Technology & Informatics
Publication Type :
Academic Journal
Accession number :
164789582
Full Text :
https://doi.org/10.3233/SHTI230573