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

被引：0
|
作者：
Yu, Guangbo [1 ]
Zhang, Zigeng [2 ]
Eresen, Aydin [2 ,3 ]
Hou, Qiaoming [2 ]
Amirrad, Farideh [4 ]
Webster, Sha [4 ]
Nauli, Surya [4 ,5 ]
Yaghmai, Vahid [2 ,3 ]
Zhang, Zhuoli [1 ,2 ,3 ,6 ]
机构：
[1] Univ Calif Irvine, Dept Biomed Engn, Irvine, CA 92617 USA
[2] Univ Calif Irvine, Dept Radiol Sci, Irvine, CA 92868 USA
[3] Univ Calif Irvine, Chao Family Comprehens Canc Ctr, Irvine, CA 92612 USA
[4] Chapman Univ, Harry & Diane Rinker Hlth Sci Campus, Dept Biomed & Pharmaceut Sci, Irvine, CA 92618 USA
[5] Univ Calif Irvine, Dept Med, Irvine, CA 92868 USA
[6] Univ Calif Irvine, Dept Pathol & Lab Med, Irvine, CA 92617 USA
来源：
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES | 2024年 / 25卷 / 22期
基金：
美国国家卫生研究院;
关键词：
PDAC; immunotherapy; immune checkpoint inhibitors; radiomics; artificial intelligence; deep learning; machine learning; PD-1; BLOCKADE; ANTI-CTLA-4; IMMUNOTHERAPY; PD-1/PD-L1; GUIDELINES; CRITERIA; LIGANDS; TUMORS; TRIAL;
D O I：
10.3390/ijms252212038
中图分类号：
Q5 [生物化学]; Q7 [分子生物学];
学科分类号：
071010 ; 081704 ;
摘要：
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.
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页数：14
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