@inproceedings{shaposhnikov-etal-2025-clarity,
    title = "{CLARITY}: Clinical Assistant for Routing, Inference, and Triage",
    author = "Shaposhnikov, Vladimir  and
      Nesterov, Alexandr  and
      Kopanichuk, Ilia  and
      Bakulin, Ivan  and
      Egor, Zhelvakov  and
      Abramov, Ruslan  and
      Olegovna, Tsapieva Ekaterina  and
      Bespalov, Iaroslav Radionovich  and
      Dylov, Dmitry V.  and
      Oseledets, Ivan",
    editor = "Potdar, Saloni  and
      Rojas-Barahona, Lina  and
      Montella, Sebastien",
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track",
    month = nov,
    year = "2025",
    address = "Suzhou (China)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2025.emnlp-industry.127/",
    pages = "1805--1821",
    ISBN = "979-8-89176-333-3",
    abstract = "We present CLARITY (Clinical Assistant for Routing, Inference and Triage), an AI-driven platform designed to facilitate patient-to-specialist routing, clinical consultations, and severity assessment of patient conditions. Its hybrid architecture combines a Finite State Machine (FSM) for structured dialogue flows with collaborative agents that employ Large Language Model (LLM) to analyze symptoms and prioritize referrals to appropriate specialists. Built on a modular microservices framework, CLARITY ensures safe, efficient, and robust performance, flexible and readily scalable to meet the demands of existing workflows and IT solutions in healthcare.We report integration of our clinical assistant into a large-scale national interhospital platform, with more than 55,000 content-rich userdialogues completed within the two months of deployment, 2,500 of which were expert-annotated for subsequent validation. The validation results show that CLARITY surpasses human-level performance in terms of the first-attempt routing precision, naturally requiring up to 3 times shorter duration of the consultation than with a human."
}