mlsanityData to 7 Oct 2026

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

arXiv 2402.04620 ↗First posted 7 Feb 2024cs.HC cs.LGcited by 9

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Abstract (arXiv)

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. CataractBot answers cataract surgery related questions instantly using an LLM to query a curated knowledge base, and provides expert-verified responses asynchronously. It has multimodal and multilingual capabilities. In an in-the-wild deployment study with 49 patients and attendants, 4 doctors, and 2 patient coordinators, CataractBot demonstrated potential, 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 expert-mediated LLM bots.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 9 of its 135 references that are in the map. First posted on arXiv 7 Feb 2024.

Builds on

9 of 135 references.

References · 9

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  2. 2020Recipes for building an open-domain chatbotcited by 593
  3. 2023MEGA: Multilingual Evaluation of Generative AIcited by 291
  4. 2023MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journalingcited by 50
  5. 2021"Brilliant AI Doctor" in Rural China: Tensions and Challenges in AI-Powered CDSS Deploymentcited by 28
  6. 2023What can we learn from Data Leakage and Unlearning for Law?cited by 15
  7. 2023Powering an AI Chatbot with Expert Sourcing to Support Credible Health Information Accesscited by 9
  8. 2018A Conversational Interface to Improve Medication Adherence: Towards AI Support in Patient's Treatmentcited by 5
  9. 2023PwR: Exploring the Role of Representations in Conversational Programmingcited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 5; 2026: 2.

9 papers.