ArticleFrontiers in medicine2025
Navigating the potential and pitfalls of large language models in patient-centered medication guidance and self-decision support.
Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Preliminary Evaluation of a Large Language Model-Powered Chatbot for Osteoporosis Self-Management Education: Formative Randomized Controlled Trial.JMIR formative research · 2026Trial
- Large Language Model Responses to Common Otolaryngological Questions: Evaluating Accuracy, Appropriateness, Readability, and Hallucinations.Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery · 2026Observational
- The Risks to Patients Associated with Using Artificial Intelligence Tools in Pharmacy Practice: A Scoping Review.Pharmacy (Basel, Switzerland) · 2026Review
- Accuracy of large language model transcription of simulated physician-patient verbal interactions.BMC medical informatics and decision making · 2026Article
- Large Language Models in Cardiovascular Prevention: A Narrative Review and Governance Framework.Diagnostics (Basel, Switzerland) · 2026Review
- Closing the loop: human-augmented, mechanistically enhanced AI for proactive management of drug-drug interactions.Frontiers in pharmacology · 2026Article
- Artificial intelligence in migraine: a narrative review on the diagnostic, prognostic, and therapeutic applications.Oxford open neuroscience · 2026Article
- Assessing Patient Education Materials for Colorectal Cancer Generated by Four Large Language Models: Readability, Quality, and Transparency Challenges.Journal of cancer education : the official journal of the American Association for Cancer Education · 2025Article
- The perils of politeness: how large language models may amplify medical misinformation.NPJ digital medicine · 2025Article
- A longitudinal analysis of declining medical safety messaging in generative AI models.NPJ digital medicine · 2025Article
- ChatGPT-4o and 4o1 Preview as Dietary Support Tools in a Real-World Medicated Obesity Program: A Prospective Comparative Analysis.Healthcare (Basel, Switzerland) · 2025Article
- E-RespiNet: An LLM-ELECTRA driven triple-stream CNN with feature fusion for asthma classification.PloS one · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large Language Models (LLMs) are transforming patient education in medication management by providing accessible information to support healthcare decision-making. Building on our recent scoping review of LLMs in patient education, this perspective examines their specific role in medication guidance. These artificial intelligence (AI)-driven tools can generate comprehensive responses about drug interactions, side effects, and emergency care protocols, potentially enhancing patient autonomy in medication decisions. However, significant challenges exist, including the risk of misinformation and the complexity of providing accurate drug information without access to individual patient data. Safety concerns are particularly acute when patients rely solely on AI-generated advice for self-medication decisions. This perspective analyzes current capabilities, examines critical limitations, and raises questions regarding the possible integration of LLMs in medication guidance. We emphasize the need for regulatory oversight to ensure these tools serve as supplements to, rather than replacements for, professional healthcare guidance.
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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.