The Applications of Artificial Intelligence in Digestive System Neoplasms: A Review

Overview

Journal Health Data Sci

Specialty Medical Informatics

Date 2024 Mar 15

PMID 38487199

Authors

Shuaitong Zhang

Wei Mu

Di Dong

Jingwei Wei

Mengjie Fang

Lizhi Shao

Yu Zhou

Bingxi He

Song Zhang

Zhenyu Liu

Jianhua Liu

Jie Tian

Affiliations

Soon will be listed here.

Abstract

Importance: Digestive system neoplasms (DSNs) are the leading cause of cancer-related mortality with a 5-year survival rate of less than 20%. Subjective evaluation of medical images including endoscopic images, whole slide images, computed tomography images, and magnetic resonance images plays a vital role in the clinical practice of DSNs, but with limited performance and increased workload of radiologists or pathologists. The application of artificial intelligence (AI) in medical image analysis holds promise to augment the visual interpretation of medical images, which could not only automate the complicated evaluation process but also convert medical images into quantitative imaging features that associated with tumor heterogeneity.

Highlights: We briefly introduce the methodology of AI for medical image analysis and then review its clinical applications including clinical auxiliary diagnosis, assessment of treatment response, and prognosis prediction on 4 typical DSNs including esophageal cancer, gastric cancer, colorectal cancer, and hepatocellular carcinoma.

Conclusion: AI technology has great potential in supporting the clinical diagnosis and treatment decision-making of DSNs. Several technical issues should be overcome before its application into clinical practice of DSNs.

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