Literature DB >> 32613386

Artificial intelligence in gastric cancer: a systematic review.

Peng Jin1, Xiaoyan Ji2, Wenzhe Kang1, Yang Li1, Hao Liu1, Fuhai Ma1, Shuai Ma1, Haitao Hu1, Weikun Li1, Yantao Tian3.   

Abstract

OBJECTIVE: This study aims to systematically review the application of artificial intelligence (AI) techniques in gastric cancer and to discuss the potential limitations and future directions of AI in gastric cancer.
METHODS: A systematic review was performed that follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Pubmed, EMBASE, the Web of Science, and the Cochrane Library were used to search for gastric cancer publications with an emphasis on AI that were published up to June 2020. The terms "artificial intelligence" and "gastric cancer" were used to search for the publications.
RESULTS: A total of 64 articles were included in this review. In gastric cancer, AI is mainly used for molecular bio-information analysis, endoscopic detection for Helicobacter pylori infection, chronic atrophic gastritis, early gastric cancer, invasion depth, and pathology recognition. AI may also be used to establish predictive models for evaluating lymph node metastasis, response to drug treatments, and prognosis. In addition, AI can be used for surgical training, skill assessment, and surgery guidance.
CONCLUSIONS: In the foreseeable future, AI applications can play an important role in gastric cancer management in the era of precision medicine.

Entities:  

Keywords:  Artificial intelligence; Cancer management; Diagnosis; Gastric cancer; Treatment

Mesh:

Year:  2020        PMID: 32613386     DOI: 10.1007/s00432-020-03304-9

Source DB:  PubMed          Journal:  J Cancer Res Clin Oncol        ISSN: 0171-5216            Impact factor:   4.553


  11 in total

Review 1.  Artificial intelligence in gastric cancer: a translational narrative review.

Authors:  Chaoran Yu; Ernest Johann Helwig
Journal:  Ann Transl Med       Date:  2021-02

2.  Current Evidence and Future Perspective of Accuracy of Artificial Intelligence Application for Early Gastric Cancer Diagnosis With Endoscopy: A Systematic and Meta-Analysis.

Authors:  Jiang Kailin; Jiang Xiaotao; Pan Jinglin; Wen Yi; Huang Yuanchen; Weng Senhui; Lan Shaoyang; Nie Kechao; Zheng Zhihua; Ji Shuling; Liu Peng; Li Peiwu; Liu Fengbin
Journal:  Front Med (Lausanne)       Date:  2021-03-15

Review 3.  A Systematic Review of Artificial Intelligence Techniques in Cancer Prediction and Diagnosis.

Authors:  Yogesh Kumar; Surbhi Gupta; Ruchi Singla; Yu-Chen Hu
Journal:  Arch Comput Methods Eng       Date:  2021-09-27       Impact factor: 8.171

Review 4.  Liquid Biopsy and Artificial Intelligence as Tools to Detect Signatures of Colorectal Malignancies: A Modern Approach in Patient's Stratification.

Authors:  Octav Ginghina; Ariana Hudita; Marius Zamfir; Andrada Spanu; Mara Mardare; Irina Bondoc; Laura Buburuzan; Sergiu Emil Georgescu; Marieta Costache; Carolina Negrei; Cornelia Nitipir; Bianca Galateanu
Journal:  Front Oncol       Date:  2022-03-08       Impact factor: 6.244

5.  Identification of gastric cancer with convolutional neural networks: a systematic review.

Authors:  Yuxue Zhao; Bo Hu; Ying Wang; Xiaomeng Yin; Yuanyuan Jiang; Xiuli Zhu
Journal:  Multimed Tools Appl       Date:  2022-02-18       Impact factor: 2.577

Review 6.  Research and Application of Artificial Intelligence Based on Electronic Health Records of Patients With Cancer: Systematic Review.

Authors:  Xinyu Yang; Dongmei Mu; Hao Peng; Hua Li; Ying Wang; Ping Wang; Yue Wang; Siqi Han
Journal:  JMIR Med Inform       Date:  2022-04-20

Review 7.  Pursuing Connectivity in Cardio-Oncology Care-The Future of Telemedicine and Artificial Intelligence in Providing Equity and Access to Rural Communities.

Authors:  Coralea Kappel; Moira Rushton-Marovac; Darryl Leong; Susan Dent
Journal:  Front Cardiovasc Med       Date:  2022-06-13

Review 8.  Artificial Intelligence (AI) and Internet of Medical Things (IoMT) Assisted Biomedical Systems for Intelligent Healthcare.

Authors:  Pandiaraj Manickam; Siva Ananth Mariappan; Sindhu Monica Murugesan; Shekhar Hansda; Ajeet Kaushik; Ravikumar Shinde; S P Thipperudraswamy
Journal:  Biosensors (Basel)       Date:  2022-07-25

9.  GCLDNet: Gastric cancer lesion detection network combining level feature aggregation and attention feature fusion.

Authors:  Xu Shi; Long Wang; Yu Li; Jian Wu; Hong Huang
Journal:  Front Oncol       Date:  2022-08-29       Impact factor: 5.738

Review 10.  Usefulness of artificial intelligence in gastric neoplasms.

Authors:  Ji Hyun Kim; Seung-Joo Nam; Sung Chul Park
Journal:  World J Gastroenterol       Date:  2021-06-28       Impact factor: 5.742

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