ArticleJMIR AI2025
AI-Supported Shared Decision-Making (AI-SDM): Conceptual Framework.
Article in JMIR AI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence for Predicting Treatment Response in Patients With Anxiety Disorders After Cognitive Behavioral Therapy: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- The VALUE of AI-Guided Communication: Enhancing Shared Decision-Making in Metabolic Bariatric Surgery Consultations Through a Metacognitive Framework.Obesity surgery · 2026Trial
- Generative AI Engagement and Perceived Nutrition-Oriented Feeding Practices Among Urban Indonesian Mothers: Mixed Methods Study.JMIR pediatrics and parenting · 2026Article
- Perceptions of simulated artificial intelligence in medical consultations: associations with stress, memory, and perceived credibility.NPJ digital medicine · 2026Article
- Personal Health Large Language Models and the Negotiation of Medical Authority in Clinical Care: Opportunities, Risks, and Governance.Journal of medical Internet research · 2026Article
- Bridging Data, Semantics, and Clinical Reasoning: A Knowledge Graph Framework for Pediatric Obstructive Sleep Apnea.Children (Basel, Switzerland) · 2026Article
- Transforming lung transplantation with artificial intelligence: a narrative review from organ allocation to post-transplant management.Journal of thoracic disease · 2026Review
- Design, development, and evaluation of a web-based consultation system for birth after cesarean: a mixed-method study protocol.BMC pregnancy and childbirth · 2026Article
- AI-driven high-risk pregnancy prediction: balancing early detection, anxiety, and discrimination in digital public health.Frontiers in public health · 2026Article
- Lifecycle answerability for artificial intelligence-enabled medical device software: a regulatory science perspective.Frontiers in medicine · 2026Article
- Review
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Unlabelled: Shared decision-making is central to patient-centered care but is often hampered by artificial intelligence (AI) systems that focus on technical transparency rather than delivering context-rich, clinically meaningful reasoning. Although AI explainability methods elucidate how decisions are made, they fall short of addressing the "why" that supports effective patient-clinician dialogue. To bridge this gap, we introduce artificial intelligence-supported shared decision-making (AI-SDM), a conceptual framework designed to integrate AI-based reasoning into shared decision-making to enhance care quality while preserving patient autonomy. AI-SDM is a structured, multimodel framework that synthesizes predictive modeling, evidence-based recommendations, and generative AI techniques to produce adaptive, context-sensitive explanations. The framework distinguishes conventional AI explainability from AI reasoning-prioritizing the generation of tailored, narrative justifications that inform shared decisions. A hypothetical clinical scenario in stroke management is used to illustrate how AI-SDM facilitates an iterative, triadic deliberation process between health care providers, patients, and AI outputs. This integration is intended to transform raw algorithmic data into actionable insights that directly support the decision-making process without supplanting human judgment.
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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.