Evidence map›Paper›PMID 39596108›Full record

ReviewInternational journal of molecular sciences2024

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

Guangbo Yu, Zigeng Zhang, Aydin Eresen, Qiaoming Hou, Farideh Amirrad, Sha Webster, Surya Nauli, Vahid Yaghmai, Zhuoli Zhang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Guangbo YuDepartment of Biomedical Engineering, University of California, Irvine, CA 92617, USA.
Zigeng ZhangDepartment of Radiological Sciences, University of California, Irvine, CA 92868, USA.
Aydin EresenDepartment of Radiological Sciences, University of California, Irvine, CA 92868, USA.
Qiaoming HouDepartment of Radiological Sciences, University of California, Irvine, CA 92868, USA.
Farideh AmirradDepartment of Biomedical and Pharmaceutical Sciences, Harry and Diane Rinker Health Science Campus, Chapman University, Irvine, CA 92618, USA.ORCID 0000-0002-0919-7634
Sha WebsterDepartment of Biomedical and Pharmaceutical Sciences, Harry and Diane Rinker Health Science Campus, Chapman University, Irvine, CA 92618, USA.ORCID 0000-0002-9997-9081
Surya NauliDepartment of Biomedical and Pharmaceutical Sciences, Harry and Diane Rinker Health Science Campus, Chapman University, Irvine, CA 92618, USA.
Vahid YaghmaiDepartment of Radiological Sciences, University of California, Irvine, CA 92868, USA.
Zhuoli ZhangDepartment of Biomedical Engineering, University of California, Irvine, CA 92617, USA.

Funding

Univ.of Calif., Irvine Cancer Center Support GrantP30CA062203 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI Melanie Funes · 1994 to 2026
$57.9M
MRI-Guided Dendritic-Cell-Based Vaccine Immunotherapy for Pancreatic CancerR01CA209886 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI Vahid Yaghmai, Zhuoli Zhang · 2016 to 2026
$3.3M
Image-guided Interventional Combination Liver Cancer ImmunotherapyR01CA241532 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI YAGHMAI, VAHID, ZHANG, ZHUOLI · 2020 to 2024
$1.8M
NCI NIH HHS P30 CA062203NCI NIH HHS R01 CA209886NCI NIH HHS R01 CA241532
6 · The paper itself

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.

Indexed as

Artificial IntelligenceImmune Checkpoint InhibitorsImmunotherapyPancreatic NeoplasmsHumansImmune Checkpoint Inhibitorsartificial intelligencedeep learningimmune checkpoint inhibitorsimmunotherapymachine learningPDACradiomics

Identifiers

PMID39596108
PMCPMC11593706

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.