Application of AI on cholangiocarcinoma

Cholangiocarcinoma, classified as intrahepatic, perihilar, and extrahepatic, is considered a deadly malignancy of the hepatobiliary system. Most cases of cholangiocarcinoma are asymptomatic. Therefore, early detection of cholangiocarcinoma is significant but still challenging. The routine screening...

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Main Authors: Jianhao Huang, Xuesong Bai, Yanyu Qiu, Xiaodong He
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-01-01
Series:Frontiers in Oncology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2024.1324222/full
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author Jianhao Huang
Xuesong Bai
Yanyu Qiu
Xiaodong He
author_facet Jianhao Huang
Xuesong Bai
Yanyu Qiu
Xiaodong He
author_sort Jianhao Huang
collection DOAJ
description Cholangiocarcinoma, classified as intrahepatic, perihilar, and extrahepatic, is considered a deadly malignancy of the hepatobiliary system. Most cases of cholangiocarcinoma are asymptomatic. Therefore, early detection of cholangiocarcinoma is significant but still challenging. The routine screening of a tumor lacks specificity and accuracy. With the application of AI, high-risk patients can be easily found by analyzing their clinical characteristics, serum biomarkers, and medical images. Moreover, AI can be used to predict the prognosis including recurrence risk and metastasis. Although they have some limitations, AI algorithms will still significantly improve many aspects of cholangiocarcinoma in the medical field with the development of computing power and technology.
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spelling doaj.art-198201815d974b4ab61c441f4e2d93102024-01-29T04:40:37ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2024-01-011410.3389/fonc.2024.13242221324222Application of AI on cholangiocarcinomaJianhao HuangXuesong BaiYanyu QiuXiaodong HeCholangiocarcinoma, classified as intrahepatic, perihilar, and extrahepatic, is considered a deadly malignancy of the hepatobiliary system. Most cases of cholangiocarcinoma are asymptomatic. Therefore, early detection of cholangiocarcinoma is significant but still challenging. The routine screening of a tumor lacks specificity and accuracy. With the application of AI, high-risk patients can be easily found by analyzing their clinical characteristics, serum biomarkers, and medical images. Moreover, AI can be used to predict the prognosis including recurrence risk and metastasis. Although they have some limitations, AI algorithms will still significantly improve many aspects of cholangiocarcinoma in the medical field with the development of computing power and technology.https://www.frontiersin.org/articles/10.3389/fonc.2024.1324222/fullcholangiocarcinoma (CCA)machine learning (ML)artificial intelligenceprognosisdiagnosis
spellingShingle Jianhao Huang
Xuesong Bai
Yanyu Qiu
Xiaodong He
Application of AI on cholangiocarcinoma
Frontiers in Oncology
cholangiocarcinoma (CCA)
machine learning (ML)
artificial intelligence
prognosis
diagnosis
title Application of AI on cholangiocarcinoma
title_full Application of AI on cholangiocarcinoma
title_fullStr Application of AI on cholangiocarcinoma
title_full_unstemmed Application of AI on cholangiocarcinoma
title_short Application of AI on cholangiocarcinoma
title_sort application of ai on cholangiocarcinoma
topic cholangiocarcinoma (CCA)
machine learning (ML)
artificial intelligence
prognosis
diagnosis
url https://www.frontiersin.org/articles/10.3389/fonc.2024.1324222/full
work_keys_str_mv AT jianhaohuang applicationofaioncholangiocarcinoma
AT xuesongbai applicationofaioncholangiocarcinoma
AT yanyuqiu applicationofaioncholangiocarcinoma
AT xiaodonghe applicationofaioncholangiocarcinoma