CataractBot: An LLM-Powered Expert-in-the-Loop Chatbot for Cataract
  Patients
Pragnya Ramjee Bhuvan Sachdeva Satvik Golechha Shreyas Kulkarni Geeta Fulari Kaushik Murali Mohit Jain
The healthcare landscape is evolving, with patients seeking more reliable
information about their health conditions, treatment options, and potential
risks. Despite the abundance of information sources, the digital age overwhelms
individuals with excess, often inaccurate information. Patients primarily trust
doctors and hospital staff, highlighting the need for expert-endorsed health
information. However, the pressure on experts has led to reduced communication
time, impacting information sharing. To address this gap, we propose
CataractBot, an experts-in-the-loop chatbot powered by large language models
(LLMs). Developed in collaboration with a tertiary eye hospital in India,
CataractBot answers cataract surgery related questions instantly by querying a
curated knowledge base, and provides expert-verified responses asynchronously.
CataractBot features multimodal support and multilingual capabilities. In an
in-the-wild deployment study with 49 participants, CataractBot proved valuable,
providing anytime accessibility, saving time, and accommodating diverse
literacy levels. Trust was established through expert verification. Broadly,
our results could inform future work on designing expert-mediated LLM bots.