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REVIEW article

Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
Volume 15 - 2024 | doi: 10.3389/fimmu.2024.1520398
This article is part of the Research Topic Studying the immune microenvironment of liver cancer using artificial intelligence View all 7 articles

Pinpointing the Integration of Artificial Intelligence and Liver Cancer

Provisionally accepted
Xiufeng Chu Xiufeng Chu 1*Ihtisham Bukhari Ihtisham Bukhari 2Mengxue Li Mengxue Li 2Guangyuan Li Guangyuan Li 2Jixuan Xu Jixuan Xu 2Pengyuan Zheng Pengyuan Zheng 2
  • 1 Houston Methodist Research Institute, Houston, United States
  • 2 Zhengzhou University, Zhengzhou, Henan Province, China

The final, formatted version of the article will be published soon.

    Liver cancer remains one of the most formidable challenges in modern medicine, characterized by its high incidence and mortality rate. Emerging evidence underscores the critical roles of the immune microenvironment in tumor occurrence, development, prognosis, and therapeutic responsiveness.However, the composition of the immune microenvironment of liver cancer (LC-IME) and its association with clinicopathological significance remain unelucidated. In this review, we present the recent developments related to the use of artificial intelligence (AI) for studying the immune microenvironment of liver cancer (LC-IME), focusing on the deciphering of complex highthroughput data. Additionally, we discussed the current challenges of data harmonization, algorithm interpretability for LC-IME study.

    Keywords: liver cancer, immune microenvironment, artificial intelligence, machine learning, ScRNA-seq

    Received: 31 Oct 2024; Accepted: 02 Dec 2024.

    Copyright: © 2024 Chu, Bukhari, Li, Li, Xu and Zheng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Xiufeng Chu, Houston Methodist Research Institute, Houston, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.