ReviewDiagnostics (Basel, Switzerland)2025
Optimizing Cancer Treatment: Exploring the Role of AI in Radioimmunotherapy.
Review in Diagnostics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed.
- Molecular Engineering Boosts Photon-Activated Immunotherapy for Prostate Cancer Through Concurrent Pyroptosis and cGAS-STING Pathway Activation.Angewandte Chemie (International ed. in English) · 2026Article
- Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics.Bioactive materials · 2026Review
- Review
- Radiolabeled Vitamins and Nanosystems as Potential Agents in Oncology Theranostics: Developed Approaches and Future Perspectives.Journal of personalized medicine · 2026Review
- Recent applications of artificial intelligence in cancer radiotherapy and immunotherapy: current status and future directions.Frontiers in immunology · 2026Review
- The expanding role of artificial intelligence in personalised medicine: from innovation to individualized care.Frontiers in medicine · 2026Review
- Medicinal chemistry perspectives on anticancer drug design based on clinical applications (2015-2025).RSC advances · 2025Review
- Advances and Emerging Techniques in Y-90 Radioembolization for Hepatocellular Carcinoma.Cancers · 2025Review
- Applications of artificial intelligence in cancer immunotherapy: a frontier review on enhancing treatment efficacy and safety.Frontiers in immunology · 2025Review
- Postoperative testicular metastasis in early to mid-stage gastric adenocarcinoma: a case report and literature review.Frontiers in oncology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radioimmunotherapy (RIT) is a novel cancer treatment that combines radiotherapy and immunotherapy to precisely target tumor antigens using monoclonal antibodies conjugated with radioactive isotopes. This approach offers personalized, systemic, and durable treatment, making it effective in cancers resistant to conventional therapies. Advances in artificial intelligence (AI) present opportunities to enhance RIT by improving precision, efficiency, and personalization. AI plays a critical role in patient selection, treatment planning, dosimetry, and response assessment, while also contributing to drug design and tumor classification. This review explores the integration of AI into RIT, emphasizing its potential to optimize the entire treatment process and advance personalized cancer care.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.