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Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry

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Abstract
Gastric cancer remains a significant global health concern, coercing the need for advancements in imaging techniques for ensuring accurate diagnosis and effective treatment planning. Artificial intelligence (AI) has emerged as a potent tool for gastric-cancer imaging, particularly for diagnostic imaging and body morphometry. This review article offers a comprehensive overview of the recent developments and applications of AI in gastric cancer imaging. We investigated the role of AI imaging in gastric cancer diagnosis and staging, showcasing its potential to enhance the accuracy and efficiency of these crucial aspects of patient management. Additionally, we explored the application of AI body morphometry specifically for assessing the clinical impact of gastrectomy. This aspect of AI utilization holds significant promise for understanding postoperative changes and optimizing patient outcomes. Furthermore, we examine the current state of AI techniques for the prognosis of patients with gastric cancer. These prognostic models leverage AI algorithms to predict long-term survival outcomes and assist clinicians in making informed treatment decisions. However, the implementation of AI techniques for gastric cancer imaging has several limitations. As AI continues to evolve, we hope to witness the translation of cutting-edge technologies into routine clinical practice, ultimately improving patient care and outcomes in the fight against gastric cancer.
Issued Date
2023
Kyung Won Kim
Jimi Huh
Bushra Urooj
Jeongjin Lee
Jinseok Lee
In-Seob Lee
Hyesun Park
Seongwon Na
Yousun Ko
Type
Article
Keyword
Artificial intelligenceDeep learningDiagnostic imagingGastric cancerSarcopenia
DOI
10.5230/jgc.2023.23.e30
URI
https://oak.ulsan.ac.kr/handle/2021.oak/17193
Publisher
JOURNAL OF GASTRIC CANCER
Language
영어
ISSN
2093-582X
Citation Volume
23
Citation Number
3
Citation Start Page
388
Citation End Page
399
Appears in Collections:
Medicine > Nursing
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