ReviewFrontiers in immunology2025
Applications of artificial intelligence in cancer immunotherapy: a frontier review on enhancing treatment efficacy and safety.
Review in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Precision Medicine and Artificial Intelligence in Next-Generation Cancer Surgery: A Comprehensive Analysis of Clinical Applications, Therapeutic Outcomes, and Implementation Strategies.Asian Pacific journal of cancer prevention : APJCP · 2025Pooled it
- Checkpoint inhibition and beyond: Precision immune engineering for the immune-privileged landscape of ocular malignancies.BioImpacts : BI · 2026Review
- CAR-T cells in solid tumors: engineering, biomarkers, translational pathways and the road ahead.Frontiers in immunology · 2026Review
- Pharmacological strategies to overcome immune checkpoint inhibitor resistance in non-small cell lung cancer.Frontiers in oncology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer immunotherapy represents a major breakthrough in oncology, particularly with immune checkpoint inhibitors (ICIs) and CAR-T cell therapies. Despite improved outcomes, challenges such as immune-related adverse events (irAEs) and treatment resistance limit clinical use. Artificial intelligence (AI) offers new opportunities to address these barriers, including target identification, efficacy prediction, toxicity monitoring, and personalized treatment design. This review highlights recent advances in AI applications for biomarker discovery, safety evaluation, gene editing, nanotechnology, and microbiome modulation, integrating evidence from clinical and preclinical studies. We also discuss future directions and challenges in applying AI to cancer immunotherapy, aiming to support further research and clinical translation.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.