Healthcare Copilot: A Modular Framework for Safe and Dynamic Medical Consultations Using Large Language Models

Abstract

This paper introduces a modular Healthcare Copilot system powered by large language models (LLMs), designed to enhance the quality, safety, and accuracy of medical consultations. The system is composed of three principal components: a Dialogue Module for interactive engagement, a Memory Module for contextual continuity, and a Processing Module for automated summarization and reporting. Evaluated across simulated tele-health scenarios, the Copilot demonstrates superior performance in coherence, inquiry depth, response accuracy, and ethical compliance compared to baseline LLMs. This framework offers a scalable solution for LLM deployment in medical assistance, eliminating the need for extensive fine-tuning while enabling structured, expert-supervised interactions.

Ähnliche Arbeiten