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

• Main Authors: Ramjee, Pragnya, Sachdeva, Bhuvan, Golechha, Satvik, Kulkarni, Shreyas, Fulari, Geeta, Murali, Kaushik, Jain, Mohit
• Format: Journal Article
• Language: English
• Published: 07-02-2024
• Subjects: Computer Science - Human-Computer Interaction; Computer Science - Learning
• DOI: 10.48550/arxiv.2402.04620

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.