Artificial intelligence in theranostics of gastric cancer, a review

Zha Yiqian; Xue Cuili; Liu Yanlei; Ni Jian; De La Fuente Jesus M.; Cui Daxiang

doi:10.1515/mr-2022-0042

Medical Review (Jun 2023)

Artificial intelligence in theranostics of gastric cancer, a review

Zha Yiqian,
Xue Cuili,
Liu Yanlei,
Ni Jian,
De La Fuente Jesus M.,
Cui Daxiang

Affiliations

Zha Yiqian: Institute of Nano Biomedicine and Engineering, Shanghai Engineering Research Center for Intelligent Diagnosis and Treatment Instrument, School of Sensing Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
Xue Cuili: Institute of Nano Biomedicine and Engineering, Shanghai Engineering Research Center for Intelligent Diagnosis and Treatment Instrument, School of Sensing Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
Liu Yanlei: Institute of Nano Biomedicine and Engineering, Shanghai Engineering Research Center for Intelligent Diagnosis and Treatment Instrument, School of Sensing Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
Ni Jian: Institute of Nano Biomedicine and Engineering, Shanghai Engineering Research Center for Intelligent Diagnosis and Treatment Instrument, School of Sensing Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
De La Fuente Jesus M.: Institute of Aragon Nanoscience, University of Zaragoza, Zaragoza, Spain
Cui Daxiang: Institute of Nano Biomedicine and Engineering, Shanghai Engineering Research Center for Intelligent Diagnosis and Treatment Instrument, School of Sensing Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

DOI: https://doi.org/10.1515/mr-2022-0042
Journal volume & issue: Vol. 3, no. 3
pp. 214 – 229

Abstract

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Gastric cancer (GC) is one of the commonest cancers with high morbidity and mortality in the world. How to realize precise diagnosis and therapy of GC owns great clinical requirement. In recent years, artificial intelligence (AI) has been actively explored to apply to early diagnosis and treatment and prognosis of gastric carcinoma. Herein, we review recent advance of AI in early screening, diagnosis, therapy and prognosis of stomach carcinoma. Especially AI combined with breath screening early GC system improved 97.4 % of early GC diagnosis ratio, AI model on stomach cancer diagnosis system of saliva biomarkers obtained an overall accuracy of 97.18 %, specificity of 97.44 %, and sensitivity of 96.88 %. We also discuss concept, issues, approaches and challenges of AI applied in stomach cancer. This review provides a comprehensive view and roadmap for readers working in this field, with the aim of pushing application of AI in theranostics of stomach cancer to increase the early discovery ratio and curative ratio of GC patients.

Published in Medical Review

ISSN: 2097-0773 (Print); 2749-9642 (Online)
Publisher: De Gruyter
Country of publisher: Germany
LCC subjects: Medicine
Website: https://www.degruyter.com/journal/key/mr/html

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