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Updated: May 12, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
Published on: December 6, 2024
Patient agency and large language models in worldwide encoding of equity
Antonis A Armoundas1,2, Joseph Loscalzo3,4
1Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. armoundas.antonis@mgh.harvard.edu.
Abstract:
Large language models progressively result in improved ways of patient engagement and access to healthcare, reaching both an exciting and concerning time, as they no longer serve solely as a guide to clinicians, but, for the first time enable patients to make decisions that directly affect their health. We present the benefits and risks of this paradigm-shift in the practice of medicine, that offers the possibility of promoting health equity.
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