⚡ Quick Summary
This scoping review synthesizes evidence on the clinical applications of generative artificial intelligence (GenAI) in head and neck oncology, highlighting its role as an assistive tool rather than an autonomous decision-maker. The findings indicate that while GenAI shows promise in structured tasks, it is not yet ready for independent clinical use.
🔍 Key Details
- 📅 Study Period: January 1, 2020 – December 15, 2025
- 🔍 Databases Used: PubMed and Scopus
- 🧩 Focus Areas: TNM staging, treatment planning, tumor board support, patient education
- 📊 Study Design: Simulation-based and small cohort studies
🔑 Key Takeaways
- 🧠 GenAI excels in structured, language-based tasks like clinical documentation and case summarization.
- 📉 Moderate agreement with clinical standards for TNM staging, but reduced reliability in complex cases.
- 📋 Tumor board support shows variable treatment recommendations from GenAI.
- 📖 Patient-facing outputs are generally readable but may lack accuracy or completeness.
- ⚠️ Limitations include hallucination, omission of key clinical factors, and overgeneralization.
- 🔄 Need for standardized validation before safe clinical adoption of GenAI tools.
📚 Background
The integration of artificial intelligence in healthcare has been a topic of great interest, particularly in oncology. Generative AI, especially large language models, has the potential to enhance clinical workflows and patient care. However, understanding its current capabilities and limitations is crucial for its effective application in head and neck cancer care.
🗒️ Study
This scoping review aimed to evaluate the current evidence surrounding the use of GenAI in head and neck oncology. The researchers conducted structured searches across relevant databases, focusing on studies that assessed the application of GenAI in various clinical tasks. The review highlights the early-stage nature of the evidence and the need for further research.
📈 Results
The findings reveal that while GenAI performs well in structured tasks, the evidence remains heterogeneous and primarily based on simulation studies. For instance, moderate agreement with clinical standards was noted for TNM staging, but the reliability diminished in more complex scenarios. Additionally, GenAI’s outputs in tumor board settings were variable, indicating a need for caution in clinical decision-making.
🌍 Impact and Implications
The implications of this study are significant for the future of oncology. While GenAI can assist in various tasks, its current limitations underscore the importance of human oversight in clinical settings. As the technology evolves, ongoing evaluation and integration into clinical workflows will be essential to ensure patient safety and effective care.
🔮 Conclusion
This review highlights the potential of generative AI as an assistive tool in head and neck oncology, while also emphasizing that it is not yet suitable for autonomous clinical decision-making. Future research should focus on prospective evaluations and standardized validation to pave the way for safe clinical adoption of these technologies.
💬 Your comments
What are your thoughts on the role of generative AI in oncology? Do you see it as a valuable assistive tool, or do you have concerns about its limitations? Let’s engage in a discussion! 💬 Share your insights in the comments below or connect with us on social media:
Assistive, not autonomous: Generative artificial intelligence in head and neck cancer care – A scoping review.
Abstract
OBJECTIVES: To synthesize current evidence on the clinical applications of generative artificial intelligence (GenAI), particularly large language models (LLMs), in head and neck oncology, with a focus on translational readiness, clinical safety, and real-world applicability.
METHODS: A scoping review was conducted using structured searches of PubMed and Scopus for studies published between January 1, 2020, and December 15, 2025. Search strategies combined controlled vocabulary and free-text terms related to generative AI and head and neck oncology. Eligible studies evaluated GenAI/LLMs in tasks including TNM staging, treatment planning, tumor board support, and patient education. Non-GenAI and non-oncologic studies were excluded. Following duplicate removal, records underwent title and abstract screening with full-text review of potentially relevant studies. Due to heterogeneity in study design, outcomes, and reporting, findings were synthesized qualitatively.
RESULTS: Evidence remains early-stage and heterogeneous, dominated by simulation-based and small cohort studies with limited real-world validation. GenAI performs best in structured, language-based tasks such as clinical documentation, case summarization, and patient education. Moderate agreement with clinical standards is reported for TNM staging and guideline navigation in common scenarios, with reduced reliability in complex cases. In tumor board settings, GenAI supports summarization but produces variable treatment recommendations. Patient-facing outputs are generally readable but may lack accuracy or completeness. Common limitations include hallucination, omission of key clinical factors, and overgeneralization.
CONCLUSION: GenAI shows promise as an assistive tool in head and neck oncology but is not yet suitable for autonomous clinical decision-making. Prospective, workflow-integrated evaluation and standardized validation are needed before safe clinical adoption.
Author: [‘Karni JE’, ‘Simon C’, ‘Hack S’]
Journal: Digit Health
Citation: Karni JE, et al. Assistive, not autonomous: Generative artificial intelligence in head and neck cancer care – A scoping review. Assistive, not autonomous: Generative artificial intelligence in head and neck cancer care – A scoping review. 2026; 12:20552076261450749. doi: 10.1177/20552076261450749