ReviewFrontiers in pharmacology2026
Data-driven strategies for immunoradiotherapy in uveal melanoma: the role of artificial intelligence.
Review in Frontiers in pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
3 authors.
Funding
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Abstract
Uveal melanoma (UM) represents the most common primary intraocular malignancy in adults and remains a formidable clinical challenge due to its high metastatic potential and characteristically limited response to conventional systemic therapies. While the combination of radiotherapy and immunotherapy has emerged as a promising multimodal strategy for managing this complex malignancy, its efficacy is significantly constrained by profound individual variations in tumor biology, immune microenvironment composition, and dynamic treatment response patterns. In recent years, artificial intelligence (AI) has fundamentally transformed the landscape of precision oncology by enabling sophisticated image analysis, robust data-driven prediction, and seamless integration of heterogeneous multi-omics information. Within the specific context of uveal melanoma, AI-driven computational models have demonstrated significant potential to accurately predict therapeutic outcomes, quantitatively characterize the tumor immune microenvironment, and optimize radiotherapeutic strategies on a personalized basis. This comprehensive review critically examines and synthesizes recent progress in AI applications for immunoradiotherapy in uveal melanoma, systematically exploring their transformative potential to refine diagnostic accuracy, enhance treatment precision, and ultimately improve long-term patient outcomes through intelligent, data-driven personalized medicine approaches that bridge multiple disciplinary boundaries.
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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 OpenQuestion graph.