ArticleNPJ digital medicine2025
Responsible Artificial Intelligence governance in oncology.
Article in NPJ digital medicine, 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.
- Optimizing the delivery of radiotherapy with artificial intelligence.Nature reviews. Clinical oncology · 2026Review
- Assessing Quality Gaps and Clinician Perspectives on AI Integration in Colorectal Cancer NGS Pathways.Current oncology (Toronto, Ont.) · 2026Article
- Article
- Operationalizing the EU AI Act in a comprehensive cancer center through an institutional governance framework.NPJ digital medicine · 2026Review
- Article
- Liability Risks of Ambient Clinical Workflows With Artificial Intelligence for Clinicians, Hospitals, and Manufacturers.JCO oncology practice · 2026Article
- Prospective multi-centre evaluation of guideline-based artificial intelligence to streamline multidisciplinary tumour board.Frontiers in oncology · 2026Article
- Large Language Models in Population Oncology: A Contemporary Review on the Use of Large Language Models to Support Data Collection, Aggregation, and Analysis in Cancer Care and Research.JCO clinical cancer informatics · 2025Review
- Incorporating large language models as clinical decision support in oncology: the Woollie model.NPJ digital medicine · 2025Article
- The double-edged algorithm: A rapid review exploring the trustworthy and responsible use of generative AI in public health.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
The use of Artificial Intelligence (AI) in healthcare is expanding rapidly, including in oncology. Although generic AI development and implementation frameworks exist in healthcare, no effective governance models have been reported in oncology. Our study reports on a Comprehensive Cancer Center's Responsible AI governance model for clinical, operations, and research programs. We report our one-year AI Governance Committee results with respect to the registration and monitoring of 26 AI models (including large language models), 2 ambient AI pilots, and a review of 33 nomograms. Novel management tools for AI governance are shared, including an overall program model, model information sheet, risk assessment tool, and lifecycle management tool. Two AI model case studies illustrate lessons learned and our "Express Pass" methodology for select models. Open research questions are explored. To the best of our knowledge, this is one of the first published reports on Responsible AI governance at scale in oncology.
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.