Predicting and Monitoring Immune Checkpoint Inhibitor Therapy Using Artificial Intelligence in Pancreatic Cancer

Authors

Guangbo Yu, University of California, Irvine
Zigeng Zhang, University of California, Irvine
Aydin Eresen, University of California, Irvine
Qiaoming Hou, University of California, Irvine
Farideh Amirrad, Chapman UniversityFollow
Sha Webster, Chapman University
Surya M. Nauli, Chapman UniversityFollow
Vahid Yaghmai, University of California, Irvine
Zhuoli Zhang, University of California, Irvine

Document Type

Article

Publication Date

11-9-2024

Abstract

Pancreatic cancer remains one of the most lethal cancers, primarily due to its late diagnosis and limited treatment options. This review examines the challenges and potential of using immunotherapy to treat pancreatic cancer, highlighting the role of artificial intelligence (AI) as a promising tool to enhance early detection and monitor the effectiveness of these therapies. By synthesizing recent advancements and identifying gaps in the current research, this review aims to provide a comprehensive overview of how AI and immunotherapy can be integrated to develop more personalized and effective treatment strategies. The insights from this review may guide future research efforts and contribute to improving patient outcomes in pancreatic cancer management.

Comments

This article was originally published in International Journal of Molecular Sciences, volume 25, issue 22, in 2024. https://doi.org/10.3390/ijms252212038

Recommended Citation

Yu, G.; Zhang, Z.; Eresen, A.; Hou, Q.; Amirrad, F.;Webster, S.; Nauli, S.; Yaghmai, V.; Zhang, Z. Predicting and Monitoring Immune Checkpoint Inhibitor Therapy Using Artificial Intelligence in Pancreatic Cancer. Int. J. Mol. Sci. 2024, 25, 12038. https://doi.org/10.3390/ijms252212038

Copyright

The authors

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.