ReviewDigital health
Assistive, not autonomous: Generative artificial intelligence in head and neck cancer care - A scoping review.
Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Generative AI as interactional infrastructure for meaning-centered care in later life.Frontiers in psychiatry · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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.