Neuroeconomics and myopia prevention: A framework for public health intervention.
Authors: Li DL, Guo TH, Grzybowski A, Pan CW
Journal: Acta ophthalmologica
mental health
psychology
open access
Abstract
Generative artificial intelligence (AI) and large language models (LLMs) have revolutionized easy public access to information about medical illnesses and treatments. For patients, LLMs can summarize information from hundreds of online resources and generate friendly human‐like text responses regarding their medical condition. Thus, the use of AI by patients is becoming increasingly popular. A rising quandary now exists since many different LLMs are readily available to give patients medical opinions in how to diagnose and manage medical conditions (common sites include ChatGPT, Claude, Copilot, DeepSeek, Gemini, Grok, etc.). Answers generated by AI can sometimes be assertive in nature and thus can skew a patient's opinion, resulting in a discrepancy with the physician's evaluation and their diagnosis or recommended management plans. This can be quite daunting to patients and challenging for physicians to respond to in clinic. In this Triological Best Practices article, we attempt to address practical ways one could respond to such a clinical encounter.