Cargando…

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

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 ima...

Descripción completa

Detalles Bibliográficos
Autores principales: Kim, Kyung Won, Huh, Jimi, Urooj, Bushra, Lee, Jeongjin, Lee, Jinseok, Lee, In-Seob, Park, Hyesun, Na, Seongwon, Ko, Yousun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Gastric Cancer Association 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10412978/
https://www.ncbi.nlm.nih.gov/pubmed/37553127
http://dx.doi.org/10.5230/jgc.2023.23.e30
_version_ 1785087034051788800
author Kim, Kyung Won
Huh, Jimi
Urooj, Bushra
Lee, Jeongjin
Lee, Jinseok
Lee, In-Seob
Park, Hyesun
Na, Seongwon
Ko, Yousun
author_facet Kim, Kyung Won
Huh, Jimi
Urooj, Bushra
Lee, Jeongjin
Lee, Jinseok
Lee, In-Seob
Park, Hyesun
Na, Seongwon
Ko, Yousun
author_sort Kim, Kyung Won
collection PubMed
description 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.
format Online
Article
Text
id pubmed-10412978
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher The Korean Gastric Cancer Association
record_format MEDLINE/PubMed
spelling pubmed-104129782023-08-11 Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry Kim, Kyung Won Huh, Jimi Urooj, Bushra Lee, Jeongjin Lee, Jinseok Lee, In-Seob Park, Hyesun Na, Seongwon Ko, Yousun J Gastric Cancer Review Article 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. The Korean Gastric Cancer Association 2023-07 2023-07-31 /pmc/articles/PMC10412978/ /pubmed/37553127 http://dx.doi.org/10.5230/jgc.2023.23.e30 Text en Copyright © 2023. Korean Gastric Cancer Association https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Kim, Kyung Won
Huh, Jimi
Urooj, Bushra
Lee, Jeongjin
Lee, Jinseok
Lee, In-Seob
Park, Hyesun
Na, Seongwon
Ko, Yousun
Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry
title Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry
title_full Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry
title_fullStr Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry
title_full_unstemmed Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry
title_short Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry
title_sort artificial intelligence in gastric cancer imaging with emphasis on diagnostic imaging and body morphometry
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10412978/
https://www.ncbi.nlm.nih.gov/pubmed/37553127
http://dx.doi.org/10.5230/jgc.2023.23.e30
work_keys_str_mv AT kimkyungwon artificialintelligenceingastriccancerimagingwithemphasisondiagnosticimagingandbodymorphometry
AT huhjimi artificialintelligenceingastriccancerimagingwithemphasisondiagnosticimagingandbodymorphometry
AT uroojbushra artificialintelligenceingastriccancerimagingwithemphasisondiagnosticimagingandbodymorphometry
AT leejeongjin artificialintelligenceingastriccancerimagingwithemphasisondiagnosticimagingandbodymorphometry
AT leejinseok artificialintelligenceingastriccancerimagingwithemphasisondiagnosticimagingandbodymorphometry
AT leeinseob artificialintelligenceingastriccancerimagingwithemphasisondiagnosticimagingandbodymorphometry
AT parkhyesun artificialintelligenceingastriccancerimagingwithemphasisondiagnosticimagingandbodymorphometry
AT naseongwon artificialintelligenceingastriccancerimagingwithemphasisondiagnosticimagingandbodymorphometry
AT koyousun artificialintelligenceingastriccancerimagingwithemphasisondiagnosticimagingandbodymorphometry