Artificial Intelligence Applications in the Treatment of Colorectal Cancer: A Narrative Review

Author:

Yang Jiaqing12,Huang Jing3,Han Deqian4,Ma Xuelei1ORCID

Affiliation:

1. Department of Biotherapy, West China Hospital and State Key Laboratory of Biotherapy, Sichuan University, Chengdu, China

2. West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China

3. Department of Ultrasound, West China Hospital, Sichuan University, Chengdu, China

4. Department of Oncology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China

Abstract

Colorectal cancer is the third most prevalent cancer worldwide, and its treatment has been a demanding clinical problem. Beyond traditional surgical therapy and chemotherapy, newly revealed molecular mechanisms diversify therapeutic approaches for colorectal cancer. However, the selection of personalized treatment among multiple treatment options has become another challenge in the era of precision medicine. Artificial intelligence has recently been increasingly investigated in the treatment of colorectal cancer. This narrative review mainly discusses the applications of artificial intelligence in the treatment of colorectal cancer patients. A comprehensive literature search was conducted in MEDLINE, EMBASE, and Web of Science to identify relevant papers, resulting in 49 articles being included. The results showed that, based on different categories of data, artificial intelligence can predict treatment outcomes and essential guidance information of traditional and novel therapies, thus enabling individualized treatment strategy selection for colorectal cancer patients. Some frequently implemented machine learning algorithms and deep learning frameworks have also been employed for long-term prognosis prediction in patients with colorectal cancer. Overall, artificial intelligence shows encouraging results in treatment strategy selection and prognosis evaluation for colorectal cancer patients.

Publisher

SAGE Publications

Subject

Oncology

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