ArticleCurrent oncology (Toronto, Ont.)2023
The Use of Artificial Intelligence in Clinical Care: A Values-Based Guide for Shared Decision Making.
Article in Current oncology (Toronto, Ont.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses 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, 2 syntheses or guidelines pooled it.
- Artificial Intelligence and Decision-Making in Oncology: A Review of Ethical, Legal, and Informed Consent Challenges.Current oncology reports · 2025Pooled it
- The Advent of Artificial Intelligence into Cardiac Surgery: A Systematic Review of Our Understanding.Brazilian journal of cardiovascular surgery · 2024Pooled it
- Artificial Intelligence Scribes in Orthopaedic Surgery: A Narrative Review.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2026Review
- The IMPACT framework for evaluating generative AI in critical care: development and multinational consensus validation.Annals of intensive care · 2026Article
- Informed Consent for Ambient Documentation Using Generative AI in Ambulatory Care.JAMA network open · 2025Article
- From Algorithms to Insight: The Transformative Power of Artificial Intelligence and Machine Learning in Urological Cancer Research.Current oncology (Toronto, Ont.) · 2025Article
- Leveraging artificial intelligence for collaborative care planning: Innovations and impacts in shared decision-making - A systematic review.Open medicine (Warsaw, Poland) · 2025Review
- Acceptance of Digital Health Technologies in Palliative Care Patients.Palliative medicine reports · 2024Article
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
Clinical applications of artificial intelligence (AI) in healthcare, including in the field of oncology, have the potential to advance diagnosis and treatment. The literature suggests that patient values should be considered in decision making when using AI in clinical care; however, there is a lack of practical guidance for clinicians on how to approach these conversations and incorporate patient values into clinical decision making. We provide a practical, values-based guide for clinicians to assist in critical reflection and the incorporation of patient values into shared decision making when deciding to use AI in clinical care. Values that are relevant to patients, identified in the literature, include trust, privacy and confidentiality, non-maleficence, safety, accountability, beneficence, autonomy, transparency, compassion, equity, justice, and fairness. The guide offers questions for clinicians to consider when adopting the potential use of AI in their practice; explores illness understanding between the patient and clinician; encourages open dialogue of patient values; reviews all clinically appropriate options; and makes a shared decision of what option best meets the patient's values. The guide can be used for diverse clinical applications of AI.
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.