Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2022 Feb 24;13(2):125-134.
doi: 10.5306/wjco.v13.i2.125.

Artificial intelligence and cholangiocarcinoma: Updates and prospects

Affiliations
Review

Artificial intelligence and cholangiocarcinoma: Updates and prospects

Hossein Haghbin et al. World J Clin Oncol. .

Abstract

Artificial intelligence (AI) is the timeliest field of computer science and attempts to mimic cognitive function of humans to solve problems. In the era of "Big data", there is an ever-increasing need for AI in all aspects of medicine. Cholangiocarcinoma (CCA) is the second most common primary malignancy of liver that has shown an increase in incidence in the last years. CCA has high mortality as it is diagnosed in later stages that decreases effect of surgery, chemotherapy, and other modalities. With technological advancement there is an immense amount of clinicopathologic, genetic, serologic, histologic, and radiologic data that can be assimilated together by modern AI tools for diagnosis, treatment, and prognosis of CCA. The literature shows that in almost all cases AI models have the capacity to increase accuracy in diagnosis, treatment, and prognosis of CCA. Most studies however are retrospective, and one study failed to show AI benefit in practice. There is immense potential for AI in diagnosis, treatment, and prognosis of CCA however limitations such as relative lack of studies in use by human operators in improvement of survival remains to be seen.

Keywords: Artificial intelligence; Cholangiocarcinoma; Diagnosis; Machine learning; Prognosis; Treatment.

PubMed Disclaimer

Conflict of interest statement

Conflict-of-interest statement: Authors have no conflict of interest.

Figures

Figure 1
Figure 1
Application of artificial intelligence in addressing cholangiocarcinoma. LR: Logistic regression; SVM: Support-vector machine.

Similar articles

Cited by

References

    1. Hulsen T, Jamuar SS, Moody AR, Karnes JH, Varga O, Hedensted S, Spreafico R, Hafler DA, McKinney EF. From Big Data to Precision Medicine. Front Med (Lausanne) 2019;6:34. - PMC - PubMed
    1. Goodfellow I, Bengio Y, Courville A. Deep learning. The MIT Press, 2016.
    1. Bi Q, Goodman KE, Kaminsky J, Lessler J. What is Machine Learning? Am J Epidemiol. 2019;188:2222–2239. - PubMed
    1. Kaul V, Enslin S, Gross SA. History of artificial intelligence in medicine. Gastrointest Endosc. 2020;92:807–812. - PubMed
    1. Rigby MJ. Ethical dimensions of using artificial intelligence in health care. AMA J Ethics. 2019;21:E121–E124.