Document Type
Poster
Publication Date
Fall 2024
Abstract
This project presents an AI-driven multi-agent system for managing and prioritizing patient appointments in a physician's chamber in a resource-poor setting. By employing a multi-agent architecture and a vector database, the system dynamically adapts to real-time events like patient check-ins, and supports the manual reordering of appointments. Built using Python, LangChain, and the ChromaDB vector database, the system can be accessed via a simple UI on Streamlit. The objective is to enhance patient flow, reduce wait times, and provide an adaptive and efficient appointment system in a Bangladeshi clinical setting.
Recommended Citation
Wadud, Ayman, "AI-Powered Appointment Prioritization System for Resource-Poor Settings" (2024). IPHS 391: Interdisciplinary AI Frontiers. Paper 2.
https://digital.kenyon.edu/dh_iphs_391/2
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.