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SARHAchat: An LLM-Based Chatbot for Sexual and Reproductive Health Counseling

arXiv 2510.16081 ↗First posted 17 Oct 2025cs.CY cs.AIcited by 0

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Abstract (arXiv)

While Artificial Intelligence (AI) shows promise in healthcare applications, existing conversational systems often falter in complex and sensitive medical domains such as Sexual and Reproductive Health (SRH). These systems frequently struggle with hallucination and lack the specialized knowledge required, particularly for sensitive SRH topics. Furthermore, current AI approaches in healthcare tend to prioritize diagnostic capabilities over comprehensive patient care and education. Addressing these gaps, this work at the UNC School of Nursing introduces SARHAchat, a proof-of-concept Large Language Model (LLM)-based chatbot. SARHAchat is designed as a reliable, user-centered system integrating medical expertise with empathetic communication to enhance SRH care delivery. Our evaluation demonstrates SARHAchat's ability to provide accurate and contextually appropriate contraceptive counseling while maintaining a natural conversational flow. The demo is available at https://sarhachat.com/}{https://sarhachat.com/.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 10 references that are in the map. First posted on arXiv 17 Oct 2025.

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References · 4

  1. 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,439
  2. 2023Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarizationcited by 246
  3. 2024Can AI Relate: Testing Large Language Model Response for Mental Health Supportcited by 21
  4. 2024Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlookscited by 18

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