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CataractBot: An LLM-Powered Expert-in-the-Loop Chatbot for Cataract Patients

Authors :
Ramjee, Pragnya
Sachdeva, Bhuvan
Golechha, Satvik
Kulkarni, Shreyas
Fulari, Geeta
Murali, Kaushik
Jain, Mohit
Publication Year :
2024

Abstract

The healthcare landscape is evolving, with patients seeking reliable information about their health conditions and available treatment options. Despite the abundance of information sources, the digital age overwhelms individuals with excess, often inaccurate information. Patients primarily trust medical professionals, highlighting the need for expert-endorsed health information. However, increased patient loads on experts has led to reduced communication time, impacting information sharing. To address this gap, we developed CataractBot, an experts-in-the-loop chatbot powered by LLMs, in collaboration with an eye hospital in India. CataractBot answers cataract surgery related questions instantly by querying a curated knowledge base and provides expert-verified responses asynchronously. It has multimodal and multilingual capabilities. In an in-the-wild deployment study with 55 participants, CataractBot proved valuable, providing anytime accessibility, saving time, accommodating diverse literacy levels, alleviating power differences, and adding a privacy layer between patients and doctors. Users reported that their trust in the system was established through expert verification. Broadly, our results could inform future work on designing expert-mediated LLM bots.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2402.04620
Document Type :
Working Paper