ReviewFrontiers in digital health2025
Artificial intelligence in oncology: promise, peril, and the future of patient-physician interaction.
Review in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Stakeholder experience with artificial intelligence in healthcare: a bibliometric study of satisfaction, trust, acceptance, and patient engagement.Frontiers in digital health · 2026Pooled it
- Beyond the algorithm: why oncology nursing in Asia-Pacific needs evidence-based AI evaluation.Asia-Pacific journal of oncology nursing · 2026Article
- The Use of Artificial Intelligence Chatbots by Newly Diagnosed Cancer Patients: A Descriptive Phenomenological Study.Current oncology (Toronto, Ont.) · 2026Article
- An AI-assisted, failure mode-based toolkit for proactive risk management in radiotherapy: A feasibility study.Technical innovations & patient support in radiation oncology · 2026Article
- Comment on "Replacing Multidisciplinary Team Meetings With Artificial Intelligence: Opportunities and Challenges".Journal of gastrointestinal cancer · 2026Article
- Perceived Barriers, Supportive-Care Integration, and Readiness for AI Integration in Oncology Practice: A Cross-Sectional Survey of Cancer Care Providers in Saudi Arabia.Journal of multidisciplinary healthcare · 2026Article
- Evaluating AI-generated patient education materials for endometrial cancer surgery: a comparative analysis of response quality, reliability, and readability between ChatGPT and DeepSeek models.Frontiers in public health · 2026Article
- Assistive, not autonomous: Generative artificial intelligence in head and neck cancer care - A scoping review.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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is increasingly embedded in oncology. While initial technical evaluations emphasize diagnostic accuracy and efficiency, the impact on patient-physician interaction (PPI)-the foundation of trust, communication, comprehension, and shared decision-making-remains underexplored. In this review, we studied the current development of AI technology facing both physicians and patients with a focus in cancer care. Among different AI technologies, chatbots, large language model agents, and extended reality applications have shown the promise to date. Survey data suggest oncologists recognize AI's potential to augment efficiency but remain cautious about liability and the erosion of relational care. Key to future AI success in improving cancer care critically depends on design, validation, governance, and human guidance and gatekeeping in care delivery.
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.