PainRelief.com (via Pain Relief at PainRelief.com)
PainRelief.com Interview with:Marc D. Succi, MDStrategic Innovation Leader | Mass General Brigham InnovationAssociate Chair of Innovation & Commercialization | Mass General Brigham Enterprise RadiologyCo-Director, Innovator Growth Division, Mass General Brigham InnovationAttending Radiologist | Mass General Emergency Radiology Assistant Professor of Radiology | Harvard Medical SchoolExecutive Director, Mass General Brigham MESH Incubator
PainRelief.com: What is the background for this study?
Response: This study investigates whether large language models (LLMs), such as GPT-4 and Google’s Gemini, introduce racial, ethnic, or sex-based bias when recommending opioid treatments for pain management. Existing literature highlights racial disparities in pain treatment, with Black patients often receiving less aggressive pain management compared to White patients. LLMs, as AI tools trained on large datasets, may either perpetuate these biases or help standardize treatment across diverse patient groups. This study analyzed hundreds of real-world patient cases, representing various pain conditions, to assess if race, ethnicity, or sex influenced the LLMs’ opioid treatment recommendations.
Last Updated on September 20, 2024 by PainRelief.com
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